Statistics

Bowman, A. W., Christensen, J. R., Dagneau, C., Kavousanaki, D., Millar, K., Moore, J. (2023) Human hair from the wreck of HMS Erebus of the Franklin Expedition, 1845: elemental chemistry revealed by double-ablation LA-ICP-MS Journal of Archaeological Science: Reports, 52, (doi: 10.1016/j.jasrep.2023.104270)

Lee, D. (2023) Computationally efficient localised spatial smoothing of disease rates using anisotropic basis functions and penalised regression fitting Spatial Statistics,

Hjelmskog, A., Toney, J., Scott, M., Crawford, J., Hasan, C., Winterbottom, J., Meier, P. (2023) Thriving Glasgow Portrait: A shared vision for a healthy, equitable and sustainable future (doi: 10.36399/gla.pubs.309671)

Chadwick, F. J., Haydon, D. T., Husmeier, D., Ovaskainen, O., Matthiopoulos, J. (2023) L.I.E.S. of omission: complex observation processes in ecology Trends in Ecology and Evolution, (doi: 10.1016/j.tree.2023.10.009)

Otto, P., Doğan, O., Taşpınar, S. (2023) A dynamic spatiotemporal stochastic volatility model with an application to environmental risks Econometrics and Statistics, (doi: 10.1016/j.ecosta.2023.11.002)

Lee, D., Walton, H., Evangelopoulos, D., Katsouyanni, K., Gowers, A. M., Shaddick, G., Mitsakou, C. (2023) Health impact assessment for air pollution in the presence of regional variation in effect sizes: the implications of using different meta-analytic approaches Environmental Pollution, 336, (doi: 10.1016/j.envpol.2023.122465)

Van Mechelen, I., Boulesteix, A.‐L., Dangl, R., Dean, N., Hennig, C., Leisch, F., Steinley, D., Warrens, M. J. (2023) A white paper on good research practices in benchmarking: the case of cluster analysis WIREs Data Mining and Knowledge Discovery, 13, (doi: 10.1002/widm.1511)

Gemmell, A. J., Brown, C. M., Ray, S., Small, A. (2023) Quantitative uptake in 99mTc-EDDA/HYNIC-TOC somatostatin receptor imaging – the effect of long-acting release somatostatin analogue therapy Nuclear Medicine Communications, 44, pp. 944-952. (doi: 10.1097/MNM.0000000000001746)

Mair, C., Brown, K., Beekman, E., Olowe, E., Macaulay, C. (2023) Nurturing learning development through student feedback Journal of Learning Development in Higher Education, 29, (doi: 10.47408/jldhe.vi29.1116)

Bonner, S. J., Zhang, W., Mu, J. (2023) On the identifiability of the trinomial model for mark‐recapture‐recovery studies Environmetrics, (doi: 10.1002/env.2827)

Lilly, J. M., Honkanen, H. H., Rodger, J. R., del Villar, D., Boylan, P., Green, A., Pereiro, D., Wilkie, L., Kennedy, R., Barkley, A., Rosell, R., Ó Maoiléidigh, N., O’Neill, R., Waters, C., Cotter, D., Bailey, D., Roche, W., McGill, R., Barry, J., Beck, S. V., Henderson, J., Parke, D., Whoriskey, F. G., Shields, B., Ramsden, P., Walton, S., Fletcher, M., Whelan, K., Bean, C. W., Elliott, S., Bowman, A., Adams, C. E. (2023) Migration patterns and navigation cues of Atlantic salmon post‐smolts migrating from 12 rivers through the coastal zones around the Irish Sea Journal of Fish Biology, (doi: 10.1111/jfb.15591)

Zhang, W., Ray, S. (2023) Deep Probability Contour Framework for Tumour Segmentation and Dose Painting in PET Images (doi: 10.1007/978-3-031-43901-8_51)

Carturan, B. S., Siewe, N., Cobbold, C. A., Tyson, R. C. (2023) Bumble bee pollination and the wildflower/crop trade-off: When do wildflower enhancements improve crop yield? Ecological Modelling, 484, (doi: 10.1016/j.ecolmodel.2023.110447)

Cantoni, D., Wilkie, C., Bentley, E. M., Mayora-Neto, M., Wright, E., Scott, S., Ray, S., Castillo-Olivares, J., Heeney, J. L., Mattiuzzo, G., Temperton, N. J. (2023) Correlation between pseudotyped virus and authentic virus neutralisation assays, a systematic review and meta-analysis of the literature Frontiers in Immunology, 14, (doi: 10.3389/fimmu.2023.1184362)

Di Napoli, M., Tanyas, H., Castro-Camilo, D., Calcaterra, D., Cevasco, A., Di Martire, D., Pepe, G., Brandolini, P., Lombardo, L. (2023) On the estimation of landslide intensity, hazard and density via data-driven models Natural Hazards, (doi: 10.1007/s11069-023-06153-0)

Zhang, W., Ray, S. (2023) From coarse to fine: a deep 3D probability volume contour framework for tumor segmentation and dose painting in PET images Frontiers In Radiology, 3, (doi: 10.3389/fradi.2023.1225215)

Sekhar Sen, I., Nizam, S., Ansari, A., Bowes, M., Choudhary, B., Glendell, M., Ray, S., Scott, M., Miller, C., Wilkie, C., Sinha, R. (2023) Geochemical evolution of dissolved trace elements in space and time in the Ramganga River, India Environmental Monitoring and Assessment, 195, (doi: 10.1007/s10661-023-11665-0)

Scott, E. M., Naysmith, P., Dunbar, E. (2023) Preliminary results from the Glasgow International Radiocarbon Intercomparison (GIRI) Radiocarbon, (doi: 10.1017/RDC.2023.64)

Di Campli San Vito, P., Shakeri, G., Ross, J., Yang, X., Brewster, S. (2023) Development of a Real-Time Stress Detection System for Older Adults with Heart Rate Data (doi: 10.1145/3594806.3594817)

Dalton, D., Husmeier, D., Gao, H. (2023) Physics-informed graph neural network emulation of soft-tissue mechanics computer methods in applied mechanics and engineering Computer Methods in Applied Mechanics and Engineering,

Pascall, D. J., Vink, E., Blacow, R., Bulteel, N., Campbell, A., Campbell, R., Clifford, S., Davis, C., da Silva Filipe, A., El Sakka, N., Fjodorova, L., Forrest, R., Goldstein, E., Gunson, R., Haughney, J., Holden, M. T.G., Honour, P., Hughes, J., James, E., Lewis, T., MacLean, O., McHugh, M., Mollett, G., Nyberg, T., Onishi, Y., Parcell, B., Ray, S., Robertson, D. L., Seaman, S. R., Shabaan, S., Shepherd, J. G., Smollett, K., Templeton, K., Wastnedge, E., Wilkie, C., Williams, T., The COVID-19 Genomics UK (COG-UK) Consortium, , Thomson, E. C. (2023) Directions of change in intrinsic case severity across successive SARS-CoV-2 variant waves have been inconsistent Journal of Infection, 87, pp. 128-135. (doi: 10.1016/j.jinf.2023.05.019)

Bass, A. M., Coleman, M., Waldron, S., Scott, M. (2023) Dissolved organic carbon export in a small, disturbed peat catchment: insights from long-term, high-resolution, sensor-based monitoring Limnology and Oceanography, 68, pp. 1750-1761. (doi: 10.1002/lno.12382)

McCartney, G., Hoggett, R., Walsh, D., Lee, D. (2023) How important is it to avoid indices of deprivation that include health variables in analyses of health inequalities? Public Health, 221, pp. 175-180. (doi: 10.1016/j.puhe.2023.06.028)

Foster, H. M.E., Gill, J. M.R., Mair, F. S., Celis-Morales, C. A., Jani, B. D., Nicholl, B. I., Lee, D., O'Donnell, C. A. (2023) Social connection and mortality in UK Biobank: a prospective cohort analysis BMC Medicine,

Bronk Ramsey, C., Adolphi, F., Austin, W., Bard, E., Bayliss, A., Blaauw, M., Cheng, H., Edwards, R. L., Friedrich, M., Heaton, T., Hogg, A., Hua, Q., Hughen, K., Kromer, B., Manning, S., Muscheler, R., Palmer, J., Pearson, C., Reimer, P., Reimer, R., Richards, D., Scott, M., Southon, J., Turney, C., Wacker, L. (2023) Development of the IntCal database Radiocarbon, (doi: 10.1017/RDC.2023.53)

Colombo, P., Miller, C., O'Donnell, R., Yang, X. (2023) A Multifidelity Framework for Wind Speed Data

Radvanyi, P., Miller, C., Alexander, C., Low, M., Jones, W. R., Rock, L. (2023) Computationally Efficient Ranking of Groundwater Monitoring Locations

Olowe, E., Macaulay, C., Brown, K., Beekman, E., Mair, C. (2023) Developing Feedback Literacy Minus the Assessment

Tripney, B.G., Dunbar, E., Scott, E.M., Naysmith, P. (2023) Routine quality assurance in the SUERC Radiocarbon Laboratory Radiocarbon, (doi: 10.1017/RDC.2023.45)

McBride, R., Wandy, J., Weidt, S., Rogers, S., Davies, V., Daly, R., Bryson, K. (2023) TopNEXt: automatic DDA exclusion framework for multi-sample mass spectrometry experiments Bioinformatics, 39, (doi: 10.1093/bioinformatics/btad406)

Di Campli San Vito, P., Yang, X., Brewster, S., Street, A., Fachner, J., Fernie, P., Muller-Rodriguez, L., Hung Hsu, M., Odell-Miller, H., Shaji, H., Itaborai, P., Evison, B., Farina, N., Banerjee, S., Kirke, A., Miranda, E. (2023) RadioMe: Adaptive Radio to Support People with Mild Dementia in Their Own Home (doi: 10.3233/FAIA230114)

Li, L., Gupta, M., Macaulay, V., Mukhopadhyay, I. (2023) Bayesian GWAS with Evolutionary Monte Carlo

Li, X., Yang, X., Ma, Z., Xue, J.-H. (2023) Deep metric learning for few-shot image classification: a review of recent developments Pattern Recognition, 138, (doi: 10.1016/j.patcog.2023.109381)

Rabbani, A., Gao, H., Lazarus, A., Dalton, D., Ge, Y., Mangion, K., Berry, C., Husmeier, D. (2023) Image-based estimation of the left ventricular cavity volume using deep learning and Gaussian process with cardio-mechanical applications Computerized Medical Imaging and Graphics, 106, (doi: 10.1016/j.compmedimag.2023.102203)

Gilbert, C., Browell, J., Stephen, B. (2023) Probabilistic load forecasting for the low voltage network: forecast fusion and daily peaks Sustainable Energy, Grids and Networks, 34, (doi: 10.1016/j.segan.2023.100998)

Paradinas, I., Illian, J., Smout, S. (2023) Understanding spatial effects in species distribution models PLoS ONE, 18, (doi: 10.1371/journal.pone.0285463)

Ho, A., Orton, R., Tayler, R., Asamaphan, P., Herder, V., Davis, C., Tong, L., Smollett, K., Manali, M., Allan, J., Rawlik, K., McDonald, S. E., Vink, E., Pollock, L., Gannon, L., Evans, C., McMenamin, J., Roy, K., Marsh, K., Divala, T., Holden, M. T.G., Lockhart, M., Yirrell, D., Currie, S., O'Leary, M., Henderson, D., Shepherd, S. J., Jackson, C., Gunson, R., MacLean, A., McInnes, N., Bradley-Stewart, A., Battle, R., Hollenbach, J., Henderson, P., Odam, M., Chikowore, P., Oosthuyzen, W., Chand, M., Shea Hamilton, M., Estrada-Rivadeneyra, D., Levin, M., Avramidis, N., Pairo-Castineira, E., Vitart, V., Wilkie, C., Palmarini, M., Ray, S., Robertson, D. L., da Silva Filipe, A., Willett, B. J., Breuer, J., Semple, M. G., Turner, D., Baillie, J. K., Thomson, E. C. (2023) Adeno-associated virus 2 infection in children with non-A-E hepatitis Nature, 617, pp. 555-563. (doi: 10.1038/s41586-023-05948-2)

Mair, C., Brown, K., Beekman, E., Olowe, E., Macaulay, C. (2023) Course Evaluations as a Feedback Dialogue Tool

Glendell, M., Sinha, R., Choudhary, B., Singh, M., Ray, S. (2023) Probabilistic Modelling of Water Quality in the Ramganga River, India, Informed by Sparce Observational Data (doi: 10.5194/egusphere-egu23-7990)

Neethipathi, D. K., Beniwal, A., Ganguly, P., Bass, A., Scott, M., Dahiya, R. (2023) Electrochemical Detection of Fe2+ ions in Water using 2-Dimensional g-C3N4 modified Glassy Carbon Electrode-based Sensor (doi: 10.1109/APSCON56343.2023.10101086)

Neethipathi, D. K., Beniwal, A., Bass, A., Scott, M., Dahiya, R. (2023) MoS2 modified screen printed carbon electrode based flexible electrochemical sensor for detection of copper ions in water IEEE Sensors Journal, 23, pp. 8146-8153. (doi: 10.1109/JSEN.2023.3257188)

Pascall, D. J., Vink, E., Blacow, R., Bulteel, N., Campbell, A., Campbell, R., Clifford, S., Davis, C., da Silva Filipe, A., El Sakka, N., Fjodorova, L., Forrest, R., Goldstein, E., Gunson, R., Haughney, J., Holden, M. T.G., Honour, P., Hughes, J., James, E., Lewis, T., Lycett, S., MacLean, O., McHugh, M., Mollett, G., Onishi, Y., Parcell, B., Ray, S., Robertson, D. L., Shabaan, S., Shepherd, J. G., Smollett, K., Templeton, K., Wastnedge, E., Wilkie, C., Williams, T., Thomson, E. C. (2023) The SARS-CoV-2 Alpha variant was associated with increased clinical severity of COVID-19 in Scotland: a genomics-based retrospective cohort analysis PLoS ONE, 18, (doi: 10.1371/journal.pone.0284187)

Otto, P., Steinert, R. (2023) Estimation of the spatial weighting matrix for spatiotemporal data under the presence of structural breaks Journal of Computational and Graphical Statistics, 32, pp. 696-711. (doi: 10.1080/10618600.2022.2107530)

Villejo, S. J., Illian, J. B., Swallow, B. (2023) Data fusion in a two-stage spatio-temporal model using the INLA-SPDE approach Spatial Statistics, 54, (doi: 10.1016/j.spasta.2023.100744)

McCartney, G., Hoggett, R., Walsh, D., Lee, D. (2023) How well do area-based deprivation indices identify income- and employment-deprived individuals across Great Britain today? Public Health, 217, pp. 22-25. (doi: 10.1016/j.puhe.2023.01.020)

Paun, I., Husmeier, D., Torney, C. J. (2023) Stochastic variational inference for scalable non-stationary Gaussian process regression Statistics and Computing, 33, (doi: 10.1007/s11222-023-10210-w)

Mair, C. (2023) Developing Graduate Attributes by Engaging Students with SoTL

Nguyen, H. D., Gupta, M. (2023) Finite sample inference for empirical Bayesian methods Scandinavian Journal of Statistics, (doi: 10.1111/sjos.12643)

Fassò, A., Rodeschini, J., Fusta Moro, A., Shaboviq, Q., Maranzano, P., Cameletti, M., Finazzi, F., Golini, N., Ignaccolo, R., Otto, P. (2023) Agrimonia: a dataset on livestock, meteorology and air quality in the Lombardy region, Italy Scientific Data, 10, (doi: 10.1038/s41597-023-02034-0)

Wandy, J., Mcbride, R., Rogers, S., Terzis, N., Weidt, S., van der Hooft, J. J.J., Bryson, K., Daly, R., Davies, V. (2023) Simulated-to-real benchmarking of acquisition methods in untargeted metabolomics Frontiers in Molecular Biosciences, 10, (doi: 10.3389/fmolb.2023.1130781)

Lee, D. (2023) Identifying boundaries in spatially continuous risk surfaces from spatially aggregated disease count data Annals of Applied Statistics,

Harvey, W. T., Davies, V., Daniels, R. S., Whittaker, L., Gregory, V., Hay, A. J., Husmeier, D., McCauley, J. W., Reeve, R. (2023) A Bayesian approach to incorporate structural data into the mapping of genotype to antigenic phenotype of influenza A(H3N2) viruses PLoS Computational Biology, 19, (doi: 10.1371/journal.pcbi.1010885)

Scott, E. M. (2023) Framing data science, analytics and statistics around the digital earth concept Environmetrics, 34, (doi: 10.1002/env.2732)

McEwan, M. P., Jack, E., Alexander, C., Bock, M. (2023) From statistics anxiety to SoTL: how a scholarly enquiry led to professional growth Open Scholarship of Teaching and Learning, 2, pp. 1-15. (doi: 10.56230/osotl.55)

Tragakis, A., Kaul, C., Murray-Smith, R., Husmeier, D. (2023) The Fully Convolutional Transformer for Medical Image Segmentation (doi: 10.1109/WACV56688.2023.00365)

Harke, F., Otto, P. (2023) Solar self-sufficient households as a driving factor for sustainability transformation Sustainability, 15, (doi: 10.3390/su15032734)

Jones, K.A., Paterson, C.A., Ray, S., Motherwell, D.W., Hamilton, D.J., Small, A.D., Martin, W., Goodfield, N.E.R. (2023) Beta-blockers and mechanical dyssynchrony in heart failure assessed by radionuclide ventriculography Journal of Nuclear Cardiology, 30, pp. 193-200. (doi: 10.1007/s12350-022-03142-x)

Fang, Y., Niu, M., Cheung, P., Lin, L. (2023) Extrinsic Bayesian optimization on manifolds Algorithms, 16, (doi: 10.3390/a16020117)

Muegge, R., Dean, N., Jack, E., Lee, D. (2023) National lockdowns in England: the same restrictions for all, but do the impacts on COVID-19 mortality risks vary geographically? Spatial and Spatio-Temporal Epidemiology, 44, (doi: 10.1016/j.sste.2022.100559)

Otto, P., Otto, P. (2023) What’s in a name? Significance, 20, pp. 34-37. (doi: 10.1093/jrssig/qmad010)

Dangerfield, C. E., Abrahams, I. D., Budd, C., Butchers, M., Cates, M. E., Champneys, A. R., Currie, C. S.M., Enright, J., Gog, J. R., Goriely, A., Hollingsworth, T. D., Hoyle, R. B., INI Professional Services, ., Isham, V., Jordan, J., Kaouri, M., Kavoussanakis, K., Leeks, J., Maini, P. K., Marr, C., Merritt, C., Mollison, D., Ray, S., Thompson, R. N., Wakefield, A., Wasley, D. (2023) Getting the most out of maths: How to coordinate mathematical modelling research to support a pandemic, lessons learnt from three initiatives that were part of the COVID-19 response in the UK Journal of Theoretical Biology, 557, (doi: 10.1016/j.jtbi.2022.111332)

Chen, Y., Shi, Y., Dong, M., Yang, X., Li, D., Wang, Y., Dick, R., Lv, Q., Zhao, Y., Yang, F., Gu, N., Shang, L. (2023) Over-parameterized Model Optimization with Polyak-Łojasiewicz Condition

Zhang, W., Chipperfield, J. D., Illian, J. B., Dupont, P., Milleret, C., de Valpine, P., Bischof, R. (2023) A flexible and efficient Bayesian implementation of point process models for spatial capture-recapture data Ecology, 104, (doi: 10.1002/ecy.3887)

Laxton, M. R., Rodríguez de Rivera, Ó., Soriano‐Redondo, A., Illian, J. B. (2023) Balancing structural complexity with ecological insight in spatio‐temporal species distribution models Methods in Ecology and Evolution, 14, pp. 162-172. (doi: 10.1111/2041-210x.13957)

Andrade, R., Cobbold, C. A. (2023) Heterogeneity in behaviour and movement can influence the stability of predator–prey periodic travelling waves Bulletin of Mathematical Biology, 85, (doi: 10.1007/s11538-022-01101-8)

Gaskell, J., Campioni, N., Morales, J. M., Husmeier, D., Torney, C. J. (2023) Inferring the interaction rules of complex systems with graph neural networks and approximate Bayesian computation Journal of the Royal Society: Interface, 20, (doi: 10.1098/rsif.2022.0676)

Stoner, O., Economou, T., Torres, R., Ashton, I., Brown, A. R. (2023) Quantifying spatio-temporal risk of harmful algal blooms and their impacts on bivalve shellfish mariculture using a data-driven modelling approach Harmful Algae, 121, (doi: 10.1016/j.hal.2022.102363)

Borowska, A., King, R. (2023) Semi-complete data augmentation for efficient state space model fitting Journal of Computational and Graphical Statistics, 32, pp. 19-35. (doi: 10.1080/10618600.2022.2077350)

Stoner, O., Halliday, A., Economou, T. (2023) Correcting delayed reporting of COVID-19 using the generalized-Dirichlet-multinomial method Biometrics, (doi: 10.1111/biom.13810)

Niu, M., Dai, Z., Cheung, P., Wang, Y. (2023) Intrinsic Gaussian process on unknown manifolds with probabilistic metrics Journal of Machine Learning Research, 24, pp. 1-42.

Jack, E., Mair, C. (2023) Investigating Readiness for Remote Learning in Three Cohorts of Students (doi: 10.52041/iase.icots11.T14C2)

Jack, E., Alexander, C., McArthur, D., Mair, C. (2023) Reflections on designing and delivering an online distance learning programme in the mathematical sciences MSOR Connections, 21, pp. 25-33. (doi: 10.21100/msor.v21i2.1397)

Scott, M. (2023) Uncertainty and error in radiocarbon dating Elsevier

Song, Q., Peng, Z., Ji, L., Yang, X., Li, X. (2022) Dual Prototypical Network for Robust Few-shot Image Classification (doi: 10.23919/APSIPAASC55919.2022.9979898)

Li, Z., Wang, L., Ding, S., Yang, X., Li, X. (2022) Few-Shot Classification With Feature Reconstruction Bias (doi: 10.23919/APSIPAASC55919.2022.9980086)

Robinson, J. I., Md Yusof, M. Y., Davies, V., Wild, D., Morgan, M., Taylor, J. C., El-Sherbiny, Y., Morris, D. L., Liu, L., Rawstron, A. C., Buch, M. H., Plant, D., Cordell, H. J., Isaacs, J. D., Bruce, I. N., Emery, P., Barton, A., Vyse, T. J., Barrett, J. H., Vital, E. M., Morgan, A. W. (2022) Comprehensive genetic and functional analyses of Fc gamma receptors influence on response to rituximab therapy for autoimmunity EBioMedicine, 86, (doi: 10.1016/j.ebiom.2022.104343)

Paun, I., Husmeier, D., Hopcraft, J. G. C., Masolele, M. M., Torney, C. J. (2022) Inferring spatially varying animal movement characteristics using a hierarchical continuous-time velocity model Ecology Letters, 25, pp. 2726-2738. (doi: 10.1111/ele.14117)

Zhang, W., Bonner, S. J., McCrea, R. (2022) Latent multinomial models for extended batch-mark data Biometrics, (doi: 10.1111/biom.13789)

Sullivan, M. K., Carrero, J.-J., Jani, B. D., Anderson, C., McConnachie, A., Hanlon, P., Nitsch, D., McAllister, D. A., Mair, F. S., Mark, P. B., Gasparini, A. (2022) The presence and impact of multimorbidity clusters on adverse outcomes across the spectrum of kidney function BMC Medicine, 20, (doi: 10.1186/s12916-022-02628-2)

Yang, Y., Gao, H., Berry, C., Carrick, D., Radjenovic, A., Husmeier, D. (2022) Classification of myocardial blood flow based on dynamic contrast-enhanced magnetic resonance imaging using hierarchical Bayesian models Journal of the Royal Statistical Society: Series C (Applied Statistics), 71, pp. 1085-1115. (doi: 10.1111/rssc.12568)

Dalton, D., Gao, H., Husmeier, D. (2022) Emulation of cardiac mechanics using Graph Neural Networks Computer Methods in Applied Mechanics and Engineering, 401, (doi: 10.1016/j.cma.2022.115645)

Harris, C., Brummitt, N., Cobbold, C. A., Reeve, R. (2022) Strong phylogenetic signals in global plant bioclimatic envelopes Global Ecology and Biogeography, 31, pp. 2191-2203. (doi: 10.1111/geb.13564)

Aldossari, S., Husmeier, D., Matthiopoulos, J. (2022) Transferable species distribution modelling: comparative performance of Generalised Functional Response models Ecological Informatics, 71, (doi: 10.1016/j.ecoinf.2022.101803)

Ray, S., Banerjee, A., Swift, A., Fanstone, J. W., Mamalakis, M., Vorselaars, B., Wilkie, C., Cole, J., Mackenzie, L. S., Weeks, S. (2022) A robust COVID-19 mortality prediction calculator based on Lymphocyte count, Urea, C-Reactive Protein, Age and Sex (LUCAS) with chest x-rays Scientific Reports, 12, (doi: 10.1038/s41598-022-21803-2)

Lavender, E., Aleynik, D., Dodd, J., Illian, J., James, M., Smout, S., Thorburn, J. (2022) Benthic animal-borne sensors and citizen science combine to validate ocean modelling Scientific Reports, 12, (doi: 10.1038/s41598-022-20254-z)

Garthoff, R., Otto, P. (2022) Spatiotemporal procedures for the statistical surveillance of spatial autoregressive models with heavy tails Communications in Statistics: Simulation and Computation, 51, pp. 5709-5737. (doi: 10.1080/03610918.2020.1779294)

Browell, J., Gilbert, C., Fasiolo, M. (2022) Covariance structures for high-dimensional energy forecasting Electric Power Systems Research, 211, (doi: 10.1016/j.epsr.2022.108446)

Otto, P., Schmid, W. (2022) A general framework for spatial GARCH models Statistical Papers, (doi: 10.1007/s00362-022-01357-1)

Alghamdi, A., Birch, D. J.S., Vyshemirsky, V., Rolinski, O. J. (2022) Impact of the flavonoid quercetin on β-amyloid aggregation revealed by intrinsic fluorescence Journal of Physical Chemistry B, 126, pp. 7229-7237. (doi: 10.1021/acs.jpcb.2c02763)

Yang, X., Guo, Y., Dong, M., Xue, J.-H. (2022) Towards certified robustness of distance metric learning IEEE Transactions on Neural Networks and Learning Systems, (doi: 10.1109/TNNLS.2022.3199902)

Olsen, J. R., Nicholls, N., Caryl, F., Orjuela Mendoza, J., Panis, L. I., Dons, E., Laeremans, M., Standaert, A., Lee, D., Avila-Palencia, I., de Nazelle, A., Nieuwenhuijsen, M., Mitchell, R. (2022) Day-to-day intrapersonal variability in mobility patterns and association with perceived stress: a cross-sectional study using GPS from 122 individuals in three European cities SSM - Population Health, 19, (doi: 10.1016/j.ssmph.2022.101172)

Alexander, C., Jack, E., McEwan, M., Bock, M. (2022) Exploring Statistics Anxiety in Several Introductory Statistics Courses to Understand Differences Between Types of Students and Types of Courses (doi: 10.52041/iase.icots11.T14D3)

Low, M., Alexander, C., Bock, M. (2022) Investigating Perceived Student Learning from Peer Review in Statistics Education (doi: 10.52041/iase.icots11.T14C1)

Castro-Camilo, D., Huser, R., Rue, H. (2022) Practical strategies for GEV-based regression models for extremes Environmetrics, 33, (doi: 10.1002/env.2742)

Lindgren, K., Bock, M., Alexander, C., Jack, E., Marshall, E. (2022) Statistics Students' Perspectives of Forced Online Learning (doi: 10.52041/iase.icots11.T14C3)

Elayouty, A., Scott, M., Miller, C. (2022) Time-varying functional principal components for non-stationary EpCO2 in freshwater systems Journal of Agricultural, Biological, and Environmental Statistics, 27, pp. 506-522. (doi: 10.1007/s13253-022-00494-2)

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Rodger, S., Scott, E. M., Nolan, A., Wright, A. K., Reid, J. (2021) Effect of age, breed, and sex on the health-related quality of life of owner assessed healthy dogs Frontiers in Veterinary Science, 8, (doi: 10.3389/fvets.2021.603139)

Paun, L. M., Husmeier, D. (2021) Markov chain Monte Carlo with Gaussian processes for fast parameter estimation and uncertainty quantification in a 1D fluid‐dynamics model of the pulmonary circulation International Journal for Numerical Methods in Biomedical Engineering, 37, (doi: 10.1002/cnm.3421)

Davies, V., Reid, J., Scott, E. M. (2021) Optimisation of scores generated by an online feline health–related quality of life (HRQL) instrument to assist the veterinary user interpret its results Frontiers in Veterinary Science, 7, (doi: 10.3389/fvets.2020.601304)

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Gilbert, C., Browell, J., McMillan, D. (2021) Probabilistic access forecasting for improved offshore operations International Journal of Forecasting, 37, pp. 134-150. (doi: 10.1016/j.ijforecast.2020.03.007)

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Mackenzie, L. S., Wilkie, C., Ray, S., Banerjee, A., Mamalakis, M., Swift, A. J., Vorselaars, B., Fanstone, J., Weeks, S. (2021) Can Kidney Function Be Used to Predict Survival of COVID-19 in Hospitals? Predictive Modelling in a Retrospective Cohort Study

Yang, X., Dong, M., Guo, Y., Xue, J.-H. (2021) Metric Learning for Categorical and Ambiguous Features: An Adversarial Approach (doi: 10.1007/978-3-030-67661-2_14)

Enright, J., Lee, D., Meeks, K., Pettersson, W., Sylvester, J. (2021) The complexity of finding optimal subgraphs to represent spatial correlation Springer

McElarney, Y., Rippey, B., Miller, C., Allen, M., Unwin, A. (2021) The long-term response of lake nutrient and chlorophyll concentrations to changes in nutrient loading in Ireland's largest lake, Lough Neagh Biology and Environment: Proceedings of the Royal Irish Academy, 121B, pp. 47-60. (doi: 10.3318/bioe.2021.04)

Li, X., Yan, J., Wu, J., Liu, Y., Yang, X., Ma, Z. (2020) Anti-Noise Relation Network for Few-shot Learning

Nedd, M., Browell, J., Egea-Alvarez, A., Bell, K., Hamilton, R., Wang, S., Brush, S. (2020) Operating a Zero Carbon GB Power System in 2025: Frequency and Fault Current [Annexes - Review of System and Network Issues, Frequency Stability, Power Electronic Devices and Fault Current, & Market Needs] (doi: 10.17868/74793)

Stoner, O., Economou, T. (2020) An advanced hidden Markov model for hourly rainfall time series Computational Statistics and Data Analysis, 152, (doi: 10.1016/j.csda.2020.107045)

Paun, L. M., Colebank, M. J., Olufsen, M. S., Hill, N. A., Husmeier, D. (2020) Assessing model mismatch and model selection in a Bayesian uncertainty quantification analysis of a fluid-dynamics model of pulmonary blood circulation Journal of the Royal Society: Interface, 17, (doi: 10.1098/rsif.2020.0886)

Redivo, E., Nguyen, H., Gupta, M. (2020) Bayesian clustering of skewed and multimodal data using geometric skewed normal distributions Computational Statistics and Data Analysis, 152, (doi: 10.1016/j.csda.2020.107040)

Tawn, R., Browell, J., Dinwoodie, I. (2020) Missing data in wind farm time series: properties and effect on forecasts Electric Power Systems Research, 189, (doi: 10.1016/j.epsr.2020.106640)

Nedd, M., Browell, J., Egea-Alvarez, A., Bell, K., Hamilton, R., Wang, S., Brush, S. (2020) Operating a Zero-Carbon GB Power System: Implications for Scotland (doi: 10.7488/era/756)

Lee, D., Robertson, C., Ramsay, C., Pyper, K. (2020) Quantifying the impact of the modifiable areal unit problem when estimating the health effects of air pollution Environmetrics, 31, (doi: 10.1002/env.2643)

Arnold, K. F., Davies, V., de Kamps, M., Tennant, P. W.G., Mbotwa, J., Gilthorpe, M. S. (2020) Reflection on modern methods: generalized linear models for prognosis and intervention—theory, practice and implications for machine learning International Journal of Epidemiology, 49, pp. 2074-2082. (doi: 10.1093/ije/dyaa049)

Morrow, A. J., Ford, T. J., Mangion, K., Kotecha, T., Rakhit, R., Galasko, G., Hoole, S., Davenport, A., Kharbanda, R., Ferreira, V. M., Shanmuganathan, M., Chiribiri, A., Perera, D., Rahman, H., Arnold, J. R., Greenwood, J. P., Fisher, M., Husmeier, D., Hill, N. A., Luo, X., Williams, N., Miller, L., Dempster, J., Macfarlane, P. W., Welsh, P., Sattar, N., Whittaker, A., McConnachie, A., Padmanabhan, S., Berry, C. (2020) Rationale and design of the Medical Research Council precision medicine with Zibotentan in microvascular angina (PRIZE) trial American Heart Journal, 229, pp. 70-80. (doi: 10.1016/j.ahj.2020.07.007)

Biosa, G., Giurghita, D., Alladio, E., Vincenti, M., Neocleous, T. (2020) Evaluation of forensic data using logistic regression-based classification methods and an R Shiny implementation Frontiers in Chemistry, 8, (doi: 10.3389/fchem.2020.00738)

Browell, J., Gilbert, C., Tawn, R., May, L. (2020) Quantile Combination for the EEM20 Wind Power Forecasting Competition (doi: 10.1109/EEM49802.2020.9221942)

Yang, X., Dong, M., Wang, Z., Gao, L., Zhang, L., Xue, J.-H. (2020) Data-augmented matched subspace detector for hyperspectral subpixel target detection Pattern Recognition, 106, (doi: 10.1016/j.patcog.2020.107464)

Mittell, E. A., Cobbold, C. A., Ijaz, U. Z., Kilbride, E. A., Moore, K. A., Mable, B. K. (2020) Feral populations of Brassica oleracea along Atlantic coasts in western Europe Ecology and Evolution, 10, pp. 11810-11825. (doi: 10.1002/ece3.6821)

Romano, E., Diana, A., Miller, C., O'Donnell, R. (2020) Optimally weighted L2 distances for spatially dependent functional data Spatial Statistics, 39, (doi: 10.1016/j.spasta.2020.100468)

Elliott, A., Chiu, A., Bazzi, M., Reinert, G., Cucuringu, M. (2020) Core–periphery structure in directed networks Proceedings of the Royal Society of London Series A: Mathematical, Physical and Engineering Sciences, 476, (doi: 10.1098/rspa.2019.0783)

Davies, V., Scott, E. M., Wright, A. K., Reid, J. (2020) Development of an early warning system for owners using a validated health-related quality of life (HRQL) instrument for companion animals and its use in a large cohort of dogs Frontiers in Veterinary Science, 7, (doi: 10.3389/fvets.2020.575795)

Underwood, W. G., Elliott, A., Cucuringu, M. (2020) Motif-based spectral clustering of weighted directed networks Applied Network Science, 5, (doi: 10.1007/s41109-020-00293-z)

Browell, J., Gilbert, C. (2020) ProbCast: Open-source Production, Evaluation and Visualisation of Probabilistic Forecasts (doi: 10.1109/PMAPS47429.2020.9183441)

Stoner, O., Economou, T. (2020) Multivariate hierarchical frameworks for modeling delayed reporting in count data Biometrics, 76, pp. 789-798. (doi: 10.1111/biom.13188)

Zhang, W., Bonner, S. J. (2020) On continuous‐time capture‐recapture in closed populations Biometrics, 76, pp. 1028-1033. (doi: 10.1111/biom.13185)

Katina, S., Kelly, B. D., Rojas, M. A., Sukno, F. M., McDermott, A., Hennessy, R. J., Lane, A., Whelan, P. F., Bowman, A. W., Waddington, J. L. (2020) Refining the resolution of craniofacial dysmorphology in bipolar disorder as an index of brain dysmorphogenesis Psychiatry Research, 291, (doi: 10.1016/j.psychres.2020.113243)

Banerjee, A., Ray, S., Vorselaars, B., Kitson, J., Mamalakis, M., Weeks, S., Baker, M., Mackenzie, L. S. (2020) Use of machine learning and artificial intelligence to predict SARS-CoV-2 infection from full blood counts in a population International Immunopharmacology, 86, (doi: 10.1016/j.intimp.2020.106705)

Gaskell, J., Campioni, N., Morales, J. M., Husmeier, D., Torney, C. J. (2020) Approximate Bayesian inference for individual-based models with emergent dynamics Avestia Publishing

Husmeier, D., Paun, L. M. (2020) Closed-loop effects in cardiovascular clinical decision support Avestia Publishing

Dalton, D., Lazarus, A., Husmeier, D. (2020) Comparative evaluation of different emulators for cardiac mechanics Avestia Publishing

Campioni, N., Husmeier, D., Morales, J. M., Gaskell, J., Torney, C. J. (2020) Modelling multiscale collective behavior with Gaussian processes Avestia Publishing

Lee, D. (2020) A tutorial on spatio-temporal disease risk modelling in R using Markov chain Monte Carlo simulation and the CARBayesST package Spatial and Spatio-Temporal Epidemiology, 34, (doi: 10.1016/j.sste.2020.100353)

Husmeier, D., Paun, L. M. (2020) Closed-loop effects in coupling cardiac physiological models to clinical interventions Servicio Editorial de la Universidad del País Vasco

Millar, K., Bowman, A. W. (2020) Cognitive archaeology: estimating the effects of blood-lead concentrations on the neuropsychological function of an officer of the 1845 Franklin expedition Journal of Archaeological Science: Reports, 32, (doi: 10.1016/j.jasrep.2020.102449)

Ray, S., Scott, M., Miller, C. (2020) Developing Statistical Downscaling to Improve Water Quality Understanding and Management in the Ramganga Sub-Basin

Wacker, L., Scott, E.M., Bayliss, A., Brown, D., Bard, E., Bollhalder, S., Freidrich, M., Capano, M., Cherkinsky, A., Chivall, D., Culleton, B.J., Dee, M.W., Friedrich, R., Hodgins, G.W.L., Hogg, A., Kennett, D.J., Knowles, T.D.J., Kuitems, M., Lange, T.E., Miyake, F., Nadeau, M.-J., Nakamura, T., Naysmith, J.P., Olsen, J., Omori, T., Petchey, F., Philippsen, B., Bronk Ramsey, C., Ravi Prasad, G.V., Seiler, N., Southon, J., Staff, R., Tuna, T. (2020) Findings from an in-depth annual tree-ring radiocarbon intercomparison Radiocarbon, 62, pp. 873-882. (doi: 10.1017/RDC.2020.49)

Stoner, O., Shaddick, G., Economou, T., Gumy, S., Lewis, J., Lucio, I., Ruggeri, G., Adair-Rohani, H. (2020) Global household energy model: a multivariate hierarchical approach to estimating trends in the use of polluting and clean fuels for cooking Journal of the Royal Statistical Society: Series C (Applied Statistics), 69, pp. 815-839. (doi: 10.1111/rssc.12428)

Dalton, D., Husmeier, D. (2020) Improved statistical emulation for a soft-tissue cardiac mechanical model Servicio Editorial de la Universidad del País Vasco

Borowska, A., Hoogerheide, L., Koopman, S. J., van Dijk, H. K. (2020) Partially censored posterior for robust and efficient risk evaluation Journal of Econometrics, 217, pp. 335-355. (doi: 10.1016/j.jeconom.2019.12.007)

van der Plicht, J., Bronk Ramsey, C., Heaton, T.J., Scott, E.M., Talamo, S. (2020) Recent developments in calibration for archaeological and environmental samples Radiocarbon, 62, pp. 1095-1117. (doi: 10.1017/RDC.2020.22)

Aldossari, S., Matthiopoulos, J., Husmeier, D. (2020) Statistical Modelling of Habitat Selection Servicio Editorial de la Universidad del País Vasco

Reimer, P. J., Austin, W. E.N., Baird, E., Bayliss, A., Blackwell, P. G., Bronk Ramsey, C., Butzin, M., Cheng, H., Edwards, R. L., Friedrich, M., Grootes, P. M., Guilderson, T. P., Hajdas, I., Heaton, T. J., Hogg, A. G., Hughen, K. A., Kromer, B., Manning, S. W., Muscheler, R., Palmer, J. G., Pearson, C., van der Plicht, J., Reimer, R. W., Richards, D. A., Scott, E. M., Southon, J. R., Turney, C. S.M., Wacker, L., Adolphi, F., Büntgen, U., Capano, M., Fahrni, S. M., Fogtmann-Schulz, A., Freidrich, R., Köhler, P., Kudsk, S., Miyake, F., Olsen, J., Reinig, F., Sakamoto, M., Sookdeo, A., Talamo, S. (2020) The IntCal20 Northern Hemisphere radiocarbon age calibration curve (0-55 kcal BP) Radiocarbon, 62, pp. 725-757. (doi: 10.1017/RDC.2020.41)

Heaton, T.J., Blaauw, M., Blackwell, P.G., Bronk Ramsey, C., Reimer, P.J., Scott, E.M. (2020) The IntCal20 approach to radiocarbon calibration curve construction: a new methodology using Bayesian splines and errors-in-variables Radiocarbon, 62, pp. 821-863. (doi: 10.1017/RDC.2020.46)

Wilkie, C., Belmont, J., Miller, C., Scott, M., August, T., Taylor, P. (2020) Hierarchical Species Distribution Modelling Across High Dimensional Nested Spatial Scales

Currie, M., Miller, C., Scott, M., Hills, A. (2020) Sensitivity Analysis Approaches to Investigate Uncertainty in Process-based Models, with Application to Aquaculture

Milligan, R.J., Scott, E.M., Jones, D.O.B., Bett, B.J., Jamieson, A.J., O'Brien, R., Pereira Costa, S., Rowe, G.T., Ruhl, H.A., Smith Jr., K.L., de Susanne, P., Vardaro, M.F., Bailey, D.M. (2020) Evidence for seasonal cycles in deep-sea fish abundances: A great migration in the deep SE Atlantic? Journal of Animal Ecology, 89, pp. 1593-1603. (doi: 10.1111/1365-2656.13215)

Gilbert, C., Browell, J., McMillan, D. (2020) Leveraging turbine-level data for improved probabilistic wind power forecasting IEEE Transactions on Sustainable Energy, 11, pp. 1152-1160. (doi: 10.1109/TSTE.2019.2920085)

Dong, M., Wang, Y., Yang, X., Xue, J.-H. (2020) Learning local metrics and influential regions for classification IEEE Transactions on Pattern Analysis and Machine Intelligence, 42, pp. 1522-1529. (doi: 10.1109/TPAMI.2019.2914899)

Messner, J. W., Pinson, P., Browell, J., Bjerregård, M. B., Schicker, I. (2020) Evaluation of wind power forecasts – an up-to-date view Wind Energy, 23, pp. 1461-1481. (doi: 10.1002/we.2497)

McKnight, J.A., Ochs, A., Mair, C., McKnight, O., Wright, R., Gibb, F., Cunningham, S.G., Strachan, M., Ritchie, S., McGurnaghan, S.J., Colhoun, H.M. (2020) The effect of DAFNE education, continuous subcutaneous insulin infusion, or both in a population with type 1 diabetes in Scotland Diabetic Medicine, 37, pp. 1016-1022. (doi: 10.1111/dme.14223)

Li, W., Lazarus, A., Gao, H., Martinez De Azcona Naharro, A., Fontana, M., Hawkins, P., Biswas, S., Janiczek, R., Cox, J., Berry, C., Husmeier, D., Luo, X. (2020) Analysis of cardiac amyloidosis progression using model-based markers Frontiers in Physiology, 11, (doi: 10.3389/fphys.2020.00324)

Bock, M., Alexander, C., Jack, E., McEwan, M. (2020) Study Design & Quantitative Analysis in Learning and Teaching Scholarship: Case Study Exploring Student Attitudes to Introductory Statistics

Merk, M. S., Otto, P. (2020) Estimation of anisotropic, time-varying spatial spillovers of fine particulate matter due to wind direction Geographical Analysis, 52, pp. 254-277. (doi: 10.1111/gean.12205)

Maberly, S. C., O'Donnell, R. A., Woolway, R. I., Cutler, M. E.J., Gong, M., Jones, I. D., Merchant, C. J., Miller, C. A., Politi, E., Scott, E. M., Thackeray, S. J., Tyler, A. N. (2020) Global lake thermal regions shift under climate change Nature Communications, 11, (doi: 10.1038/s41467-020-15108-z)

Hanlon, P., Quinn, T. J., Gallacher, K. I., Myint, P. K., Jani, B. D., Nicholl, B. I., Lowrie, R., Soiza, R. L., Neal, S. R., Lee, D., Mair, F. S. (2020) Assessing risks of polypharmacy involving medications with anticholinergic properties Annals of Family Medicine, 18, pp. 148-155. (doi: 10.1370/afm.2501)

Nedd, M., Browell, J., Bell, K., Booth, C. (2020) Containing a credible loss to within frequency stability limits in a low inertia GB power system IEEE Transactions on Industry Applications, 56, pp. 1031-1039. (doi: 10.1109/TIA.2019.2959996)

Nickbakhsh, S., Mair, C., Matthews, L., Reeve, R., Johnson, P.C.D., Thorburn, F., Von Wissmann, B., McMenamin, J., Gunson, R.N., Murcia, P.R. (2020) Reply to Kloepfer and Gern: Independent studies suggest an arms race between influenza and rhinovirus: what next? Proceedings of the National Academy of Sciences of the United States of America, 117, pp. 6988-6989. (doi: 10.1073/pnas.2000903117)

Sweeney, C., Bessa, R. J., Browell, J., Pinson, P. (2020) The future of forecasting for renewable energy WIREs Energy and Environment, 9, (doi: 10.1002/wene.365)

Cobbold, C. A., Stana, R. (2020) Should I stay or should I go: partially sedentary populations can outperform fully dispersing populations in response to climate-induced range shifts Bulletin of Mathematical Biology, 82, (doi: 10.1007/s11538-020-00700-7)

Subbiah, M., Caudell, M. A., Mair, C., Davis, M. A., Matthews, L., Quinlan, R. J., Quinlan, M. B., Lyimo, B., Buza, J., Keyyu, J., Call, D. R. (2020) Antimicrobial resistant enteric bacteria are widely distributed amongst people, animals and the environment in Tanzania Nature Communications, 11, (doi: 10.1038/s41467-019-13995-5)

Hanlon, P., McCallum, M., Jani, B. D., McQueenie, R., Lee, D., Mair, F. S. (2020) Association between childhood maltreatment and the prevalence and complexity of multimorbidity: a cross-sectional analysis of 157,357 UK Biobank participants Journal of Comorbidity, 10, pp. 1-12. (doi: 10.1177/2235042X10944344)

Dong, M., Yang, X., Zhu, R., Wang, Y., Xue, J.-H. (2020) Generalization Bound of Gradient Descent for Non-Convex Metric Learning

Castro-Camilo, D., Huser, R. (2020) Local likelihood estimation of complex tail dependence structures, applied to U.S. precipitation extremes Journal of the American Statistical Association, 115, pp. 1037-1054. (doi: 10.1080/01621459.2019.1647842)

Otto, P. (2019) spGARCH: An R-package for spatial and spatiotemporal ARCH and GARCH models R Journal, 11, pp. 401-420.

Nickbakhsh, S., Mair, C., Matthews, L., Reeve, R., Johnson, P.C.D., Thorburn, F., Von Wissmann, B., Reynolds, A., McMenamin, J., Gunson, R.N., Murcia, P.R. (2019) Virus-virus interactions impact the population dynamics of influenza and the common cold Proceedings of the National Academy of Sciences of the United States of America, 116, pp. 27142-27150. (doi: 10.1073/pnas.1911083116)

Mair, C., Nickbakhsh, S., Reeve, R., McMenamin, J., Reynolds, A., Gunson, R. N., Murcia, P. R., Matthews, L. (2019) Estimation of temporal covariances in pathogen dynamics using Bayesian multivariate autoregressive models PLoS Computational Biology, 15, (doi: 10.1371/journal.pcbi.1007492)

Rolinski, O. J., Alghamdi, A., Wellbrock, T., Birch, D. J.S., Vyshemirsky, V. (2019) Cu2+ effects on beta‐amyloid oligomerisation monitored by fluorescence of intrinsic tyrosine ChemPhysChem, 20, pp. 3181-3185. (doi: 10.1002/cphc.201900565)

Vittert, L., Bowman, A. W., Katina, S. (2019) A hierarchical curve-based approach to the analysis of manifold data Annals of Applied Statistics, 13, pp. 2539-2563. (doi: 10.1214/19-AOAS1267)

McGrane, S. J., Acuto, M., Artioli, F., Chen, P.-Y., Comber, R., Cottee, J., Farr-Wharton, G., Green, N., Helfgott, A., Larcom, S., McCann, J. A., O'Reilly, P., Salmoral, G., Scott, M., Todman, L. C., van Gevelt, T., Yan, X. (2019) Scaling the nexus: towards integrated frameworks for analysing water, energy and food Geographical Journal, 185, pp. 419-431. (doi: 10.1111/geoj.12256)

Buckley, J., Daly, R., Cobbold, C. A., Burgess, K., Mable, B. K. (2019) Changing environments and genetic variation: natural variation in inbreeding does not compromise short-term physiological responses Proceedings of the Royal Society of London Series B: Biological Sciences, 286, (doi: 10.1098/rspb.2019.2109)

Davies, V., Noè, U., Lazarus, A., Gao, H., Macdonald, B., Berry, C., Luo, X., Husmeier, D. (2019) Fast parameter inference in a biomechanical model of the left ventricle by using statistical emulation Journal of the Royal Statistical Society: Series C (Applied Statistics), 68, pp. 1555-1576. (doi: 10.1111/rssc.12374)

Edmunds, C., Martín-Martínez, S., Browell, J., Gómez-Lázaro, E., Galloway, S. (2019) On the participation of wind energy in response and reserve markets in Great Britain and Spain Renewable and Sustainable Energy Reviews, 115, (doi: 10.1016/j.rser.2019.109360)

Browell, J., Stock, A., McMillan, D. (2019) Recommendation for the Evaluation of Wind Farm Power Available Signal Accuracy

Gilbert, C., Browell, J., McMillan, D. (2019) A Data-driven Vessel Motion Model for Offshore Access Forecasting (doi: 10.1109/OCEANSE.2019.8867176)

Wandy, J., Davies, V., van der Hooft, J. J.J., Weidt, S., Daly, R., Rogers, S. (2019) In silico optimization of mass spectrometry fragmentation strategies in metabolomics Metabolites, 9, (doi: 10.3390/metabo9100219)

Amato, G., Eisank, C., Castro-Camilo, D., Lombardo, L. (2019) Accounting for covariate distributions in slope-unit-based landslide susceptibility models. A case study in the alpine environment Engineering Geology, 260, (doi: 10.1016/j.enggeo.2019.105237)

Colebank, M. J., Paun, L. M., Qureshi, M. U., Chesler, N., Husmeier, D., Olufsen, M. S., Ellwein Fix, L. (2019) Influence of image segmentation on one-dimensional fluid dynamics predictions in the mouse pulmonary arteries Journal of the Royal Society: Interface, 16, (doi: 10.1098/rsif.2019.0284)

Napier, G., Lee, D., Robertson, C., Lawson, A. (2019) A Bayesian space–time model for clustering areal units based on their disease trends Biostatistics, 20, pp. 681-697. (doi: 10.1093/biostatistics/kxy024)

Stoner, O., Economou, T., Drummond Marques da Silva, G. (2019) A hierarchical framework for correcting under-reporting in count data Journal of the American Statistical Association, 114, pp. 1481-1492. (doi: 10.1080/01621459.2019.1573732)

Wu, M., Cai, X., Lin, J., Zhang, X., Scott, E. M., Li, X. (2019) Association between fibre intake and indoxyl sulphate/P-cresyl sulphate in patients with chronic kidney disease: meta-analysis and systematic review of experimental studies Clinical Nutrition, 38, pp. 2016-2022. (doi: 10.1016/j.clnu.2018.09.015)

Naysmith, P., Scott, E. M., Dunbar, E., Cook, G. T. (2019) Humics - their history in the radiocarbon inter-comparisons studies Radiocarbon, 61, pp. 1413-1422. (doi: 10.1017/RDC.2019.11)

Scott, E.M., Cook, G.T., Naysmith, P., Staff, R.A. (2019) Learning from the wood samples in ICS, TIRI, FIRI, VIRI and SIRI Radiocarbon, 61, pp. 1293-1304. (doi: 10.1017/RDC.2019.12)

Scott, E. M., Naysmith, P., Cook, G. T. (2019) Life after SIRI- where next? Radiocarbon, 61, pp. 1159-1168. (doi: 10.1017/RDC.2019.10)

McIntosh, A., Anderson, C. (2019) Modelling the Risk of Exceeding Air Quality Monitoring Thresholds in Scotland

Richardson, J., Feuchtmayr, H., Miller, C., Hunter, P., Maberly, S. C., Carvalho, L. (2019) The response of cyanobacteria and phytoplankton abundance to warming, extreme rainfall events and nutrient enrichment Global Change Biology, 25, pp. 3365-3380. (doi: 10.1111/gcb.14701)

Bastos, L. S., Economou, T., Gomes, M. F.C., Villela, D. A.M., Coelho, F. C., Cruz, O. G., Stoner, O., Bailey, T., Codeço, C. T. (2019) A modelling approach for correcting reporting delays in disease surveillance data Statistics in Medicine, 38, pp. 4363-4377. (doi: 10.1002/sim.8303)

Nightingale, G. F., Illian, J. B., King, R., Nightingale, P. (2019) Area interaction point processes for bivariate point patterns in a Bayesian context Journal of Environmental Statistics, 9,

Chung, L. H. C., Birch, D. J. S., Vyshemirsky, V., Ryadnov, M. G., Rolinski, O. J. (2019) Tracking insulin glycation in real time by time-resolved emission spectroscopy Journal of Physical Chemistry B, 123, pp. 7812-7817. (doi: 10.1021/acs.jpcb.9b06363)

Davies, V., Reid, J., Wiseman-Orr, M. L., Scott, E. M. (2019) Optimising outputs from a validated online instrument to measure health-related quality of life (HRQL) in dogs PLoS ONE, 14, (doi: 10.1371/journal.pone.0221869)

Marinas-Collado, I., Bowman, A., Macaulay, V. (2019) A phylogenetic Gaussian process model for the evolution of curves embedded in d-dimensions Computational Statistics and Data Analysis, 137, pp. 285-298. (doi: 10.1016/j.csda.2019.03.002)

Castro-Camilo, D., Huser, R., Rue, H. (2019) A spliced Gamma-Generalized Pareto model for short-term extreme wind speed probabilistic forecasting Journal of Agricultural, Biological and Environmental Statistics, 24, pp. 517-534. (doi: 10.1007/s13253-019-00369-z)

Zhang, W., Bravington, M.V., Fewster, R.M. (2019) Fast likelihood‐based inference for latent count models using the saddlepoint approximation Biometrics, 75, pp. 723-733. (doi: 10.1111/biom.13030)

Macdonald, B., Husmeier, D. (2019) Model selection via marginal likelihood estimation by combining thermodynamic integration and gradient matching Statistics and Computing, 29, pp. 853-867. (doi: 10.1007/s11222-018-9840-4)

Grzegorczyk, M., Husmeier, D. (2019) Modelling non-homogeneous dynamic Bayesian networks with piece-wise linear regression models Wiley

Anderson, C., Hafen, R., Sofrygin, O., Ryan, L. (2019) Comparing predictive abilities of longitudinal child growth models Statistics in Medicine, 38, pp. 3555-3570. (doi: 10.1002/sim.7693)

Anderson, C., Xiao, L., Checkley, W. (2019) Using data from multiple studies to develop a child growth correlation matrix Statistics in Medicine, 30, pp. 3540-3554. (doi: 10.1002/sim.7696)

Paun, I., Husmeier, D., Torney, C. (2019) A Study on Discrete-Time Movement Models (doi: 10.11159/icsta19.27)

Romaszko, L., Borowska, A., Lazarus, A., Gao, H., Luo, X., Husmeier, D. (2019) Direct Learning Left Ventricular Meshes from CMR Images (doi: 10.11159/icsta19.25)

Paun, L. M., Colebank, M., Qureshi, M. U., Olufsen, M., Hill, N., Husmeier, D. (2019) MCMC with Delayed Acceptance using a Surrogate Model with an Application to Cardiovascular Fluid Dynamics (doi: 10.11159/icsta19.28)

Romaszko, L., Lazarus, A., Gao, H., Borowska, A., Luo, X., Husmeier, D. (2019) Massive Dimensionality Reduction for the Left Ventricular Mesh (doi: 10.11159/icsta19.24)

Yang, Y., Gao, H., Berry, C., Radjenovic, A., Husmeier, D. (2019) Quantification of Myocardial Perfusion Lesions Using Spatially Variant Finite Mixture Modelling of DCE-MRI (doi: 10.11159/icsta19.26)

Hurford, A., Cobbold, C. A., Molnár, P. K. (2019) Skewed temperature dependence affects range and abundance in a warming world Proceedings of the Royal Society of London Series B: Biological Sciences, 286, (doi: 10.1098/rspb.2019.1157)

Husmeier, D., Lazarus, A., Noè, U., Davies, V., Borowska, A., Macdonald, B., Gao, H., Berry, C., Luo, X. (2019) Statistical Emulation of Cardiac Mechanics: an Important Step Towards a Clinical Decision Support System (doi: 10.11159/icsta19.29)

Mair, C., Wulaningsih, W., Jeyam, A., McGurnaghan, S., Blackbourn, L., Kennon, B., Leese, G., Lindsay, R., McCrimmon, R. J., McKnight, J., Petrie, J. R., Sattar, N., Wild, S. H., Conway, N., Craigie, I., Robertson, K., Bath, L., McKeigue, P. M., Colhoun, H. M. (2019) Glycaemic control trends in people with type 1 diabetes in Scotland 2004–2016 Diabetologia, 62, pp. 1375-1384. (doi: 10.1007/s00125-019-4900-7)

Davies, V., Harvey, W. T., Reeve, R., Husmeier, D. (2019) Improving the identification of antigenic sites in the H1N1 Influenza virus through accounting for the experimental structure in a sparse hierarchical Bayesian model Journal of the Royal Statistical Society: Series C (Applied Statistics), 68, pp. 859-885. (doi: 10.1111/rssc.12338)

Devlin, J., Husmeier, D., Mackenzie, J.A. (2019) Optimal estimation of drift and diffusion coefficients in the presence of static localization error Physical Review E, 100, (doi: 10.1103/PhysRevE.100.022134)

Zhang, W., Liu, J., Goodman, J., Weir, B. S., Fewster, R. M. (2019) Stationary distribution of the linkage disequilibrium coefficient r2 Theoretical Population Biology, 128, pp. 19-26. (doi: 10.1016/j.tpb.2019.05.002)

Python, A., Illian, J. B., Jones‐Todd, C. M., Blangiardo, M. (2019) The deadly facets of terrorism Significance, 16, pp. 28-31. (doi: 10.1111/j.1740-9713.2019.01300.x)

Noè, U., Lazarus, A., Gao, H., Davies, V., Macdonald, B., Mangion, K., Berry, C., Luo, X., Husmeier, D. (2019) Gaussian process emulation to accelerate parameter estimation in a mechanical model of the left ventricle: a critical step towards clinical end-user relevance Journal of the Royal Society: Interface, 16, (doi: 10.1098/rsif.2019.0114)

Al Alawi, M., Ray, S., Gupta, M. (2019) A New Framework for Distance-based Functional Clustering

Yang, X., Zhang, L., Gao, L., Xue, J.-H. (2019) MSDH: matched subspace detector with heterogeneous noise Pattern Recognition Letters, 125, pp. 701-707. (doi: 10.1016/j.patrec.2019.07.014)

Dean, N., Dong, G., Piekut, A., Pryce, G. (2019) Frontiers in residential segregation: understanding neighbourhood boundaries and their impacts Tijdschrift voor Economische en Sociale Geografie, 110, pp. 271-288. (doi: 10.1111/tesg.12316)

Niu, M., Cheung, P., Lin, L., Dai, Z., Lawrence, N., Dunson, D. (2019) Intrinsic Gaussian processes on complex constrained domains Journal of the Royal Statistical Society: Series B (Statistical Methodology), 81, pp. 603-627. (doi: 10.1111/rssb.12320)

Bayarri, M.J., Berger, J. O., Jang, W., Ray, S., Pericchi, L. R., Visser, I. (2019) Prior-based Bayesian information criterion Statistical Theory and Related Fields, 3, pp. 2-13. (doi: 10.1080/24754269.2019.1582126)

Berger, J., Jang, W., Ray, S., Rericchi, L. R., Visser, I. (2019) Rejoinder by James Berger, Woncheol Jang, Surajit Ray, Luis R. Pericchi and Ingmar Visser Statistical Theory and Related Fields, 3, pp. 37-39. (doi: 10.1080/24754269.2019.1611147)

Browell, J., Möhrlen, C., Zack, J., Messner, J. W. (2019) IEA Wind Recommended Practices for Selecting Renewable Power Forecasting Solutions: Part 3: Evaluation of Forecasts and Forecast Solutions

Ray, S. (2019) Analysis of PET Imaging for Tumor Delineation

Stefan, T., Matthews, L., Prada, J. M., Mair, C., Reeve, R., Stear, M. J. (2019) Divergent Allele Advantage provides a quantitative model for maintaining alleles with a wide range of intrinsic merits Genetics, 212, pp. 553-564. (doi: 10.1534/genetics.119.302022)

Jack, E., Lee, D., Dean, N. (2019) Estimating the changing nature of Scotland's health inequalities using a multivariate spatiotemporal model Journal of the Royal Statistical Society: Series A (Statistics in Society), 182, pp. 1061-1080. (doi: 10.1111/rssa.12447)

Lee, D., Roertson, C., Ramsay, C., Gillespie, C., Napier, G. (2019) Estimating the health impact of air pollution in Scotland, and the resulting benefits of reducing concentrations in city centres Spatial and Spatio-Temporal Epidemiology, 29, pp. 85-96. (doi: 10.1016/j.sste.2019.02.003)

Mangisa, S., Das, S., Ray, S., Sharp, G. (2019) Functional regression models for South African economic indicators: a growth curve perspective OPEC Energy Review, 43, pp. 217-237. (doi: 10.1111/opec.12148)

Soriano‐Redondo, A., Jones‐Todd, C. M., Bearhop, S., Hilton, G. M., Lock, L., Stanbury, A., Votier, S. C., Illian, J. B. (2019) Understanding species distribution in dynamic populations: a new approach using spatio‐temporal point process models Ecography, 42, pp. 1092-1102. (doi: 10.1111/ecog.03771)

Bachl, F. E., Lindgren, F., Borchers, D. L., Illian, J. B. (2019) inlabru: an R package for Bayesian spatial modelling from ecological survey data Methods in Ecology and Evolution, 10, pp. 760-766. (doi: 10.1111/2041-210X.13168)

Baştürk, N., Borowska, A., Grassi, S., Hoogerheide, L., van Dijk, H.K. (2019) Forecast density combinations of dynamic models and data driven portfolio strategies Journal of Econometrics, 210, pp. 170-186. (doi: 10.1016/j.jeconom.2018.11.011)

Wilkie, C.J., Miller, C.A., Scott, E.M., O'Donnell, R.A., Hunter, P.D., Spyrakos, E., Tyler, A.N. (2019) Nonparametric statistical downscaling for the fusion of data of different spatiotemporal support Environmetrics, 30, (doi: 10.1002/env.2549)

Jani, B. D., Hanlon, P., Nicholl, B. I., McQueenie, R., Gallacher, K. I., Lee, D., Mair, F. S. (2019) Relationship between multimorbidity, demographic factors and mortality: findings from the UK Biobank Cohort BMC Medicine, 17, (doi: 10.1186/s12916-019-1305-x)

Jayaraman, S., Harris, C., Paxton, E., Donachie, A.-M., Vaikkinen, H., McCulloch, R., Hall, J. P.J., Kenny, J., Lenzi, L., Herts-Fowler, C., Cobbold, C., Reeve, R., Micheol, T., Morrison, L. J. (2019) Application of long read sequencing to determine expressed antigen diversity in Trypanosoma brucei infections PLoS Neglected Tropical Diseases, 13, (doi: 10.1371/journal.pntd.0007262)

Sørbye, S. H., Illian, J. B., Simpson, D. P., Burslem, D., Rue, H. (2019) Careful prior specification avoids incautious inference for log-Gaussian Cox point processes Journal of the Royal Statistical Society: Series C (Applied Statistics), 68, pp. 543-564. (doi: 10.1111/rssc.12321)

Flynt, A., Dean, N. (2019) Growth mixture modeling with measurement selection Journal of Classification, 36, pp. 3-25. (doi: 10.1007/s00357-018-9275-9)

Jones-Todd, C. M., Caie, P., Illian, J. B., Stevenson, B. C., Savage, A., Harrison, D. J., Bown, J. L. (2019) Identifying prognostic structural features in tissue sections of colon cancer patients using point pattern analysis Statistics in Medicine, 38, pp. 1421-1441. (doi: 10.1002/sim.8046)

Tuchow, N. W., Ford, E. B., Papamarkou, T., Lindo, A. (2019) The efficiency of geometric samplers for exoplanet transit timing variation models Monthly Notices of the Royal Astronomical Society, 484, pp. 3772-3784. (doi: 10.1093/mnras/stz247)

Grau Andres, R., Gray, A., Davies, G. M., Scott, E. M., Waldron, S. (2019) Burning increases post-fire carbon emissions in a heathland and a raised bog, but experimental manipulation of fire severity has no effect Journal of Environmental Management, 233, pp. 321-328. (doi: 10.1016/j.jenvman.2018.12.036)

Bakka, H., Vanhatalo, J., Illian, J. B., Simpson, D., Rue, H. (2019) Non-stationary Gaussian models with physical barriers Spatial Statistics, 29, pp. 268-288. (doi: 10.1016/j.spasta.2019.01.002)

Franco-Villoria, M., Scott, M., Hoey, T. (2019) Spatiotemporal modeling of hydrological return levels: A quantile regression approach Environmetrics, 30, (doi: 10.1002/env.2522)

Flynt, A., Dean, N., Nugent, R. (2019) sARI: a soft agreement measure for class partitions incorporating assignment probabilities Advances in Data Analysis and Classification, 13, pp. 303-323. (doi: 10.1007/s11634-018-0346-x)

Möhrlen, C., Zack, J., Lerner, J., Messner, J., Browell, J., Collier, C., Tuohy, A., Sharp, J., Westenholz, M. (2019) Recommended Practices for the Implementation of Wind Power Forecasting Solutions: Part 2: Designing and Executing Forecasting Benchmarks and Trials

Möhrlen, C., Zack, J., Messner, J., Browell, J., Collier, C. (2019) Recommended Practices for the Implementation of Wind Power Forecasting Solutions: Part 3: Evaluation of Forecasts and Forecast Solutions

McLean, M.I., Evers, L., Bowman, A.W., Bonte, M., Jones, W.R. (2019) Statistical modelling of groundwater contamination monitoring data: a comparison of spatial and spatiotemporal methods Science of the Total Environment, 652, pp. 1339-1346. (doi: 10.1016/j.scitotenv.2018.10.231)

Macaulay, V., Soares, P., Richards, M. B. (2019) Rectifying long-standing misconceptions about the p statistic for molecular dating PLoS ONE, 14, (doi: 10.1371/journal.pone.0212311)

Finazzi, F., Napier, Y., Scott, M., Hills, A., Cameletti, M. (2019) A statistical emulator for multivariate model outputs with missing values Atmospheric Environment, 199, pp. 415-422. (doi: 10.1016/j.atmosenv.2018.11.025)

Ewing, D. A., Cobbold, C. A., Purse, B. V., Schafer, S. M., White, S. M. (2019) Uncovering mechanisms behind mosquito seasonality by integrating mathematical models and daily empirical population data: Culex pipiens in the UK Parasites and Vectors, 12, (doi: 10.1186/s13071-019-3321-2)

Beresford, N.A., Scott, E. M., Copplestone, D. (2019) Field effects studies in the Chernobyl Exclusion Zone: lessons to be learnt Journal of Environmental Radioactivity, (doi: 10.1016/j.jenvrad.2019.01.005)

Grau-Andrés, R., Davies, G. M., Waldron, S., Scott, E. M., Gray, A. (2019) Increased fire severity alters initial vegetation regeneration across Calluna-dominated ecosystems Journal of Environmental Management, 231, pp. 1004-1011. (doi: 10.1016/j.jenvman.2018.10.113)

Bowman, A. W. (2019) Graphics for uncertainty Journal of the Royal Statistical Society: Series A (Statistics in Society), 182, pp. 403-418. (doi: 10.1111/rssa.12379)

Umar Qureshi, M., Colebank, M. J., Paun, L. M., Ellwein, L., Chesler, N., Haider, M. A., Hill, N. A., Husmeier, D., Olufsen, M. S. (2019) Hemodynamic assessment of pulmonary hypertension in mice: a model based analysis of the disease mechanism Biomechanics and Modeling in Mechanobiology, 18, pp. 219-243. (doi: 10.1007/s10237-018-1078-8)

Borowska, A., Hoogerheide, L. F., Koopman, S. J. (2019) Bayesian Risk Forecasting for Long Horizons (doi: 10.2139/ssrn.3339819)

Python, A., Illian, J. B., Jones‐Todd, C. M., Blangiardo, M. (2019) A Bayesian approach to modelling subnational spatial dynamics of worldwide non‐state terrorism, 2010–2016 Journal of the Royal Statistical Society: Series A (Statistics in Society), 182, pp. 323-344. (doi: 10.1111/rssa.12384)

Pennino, M. G., Paradinas, I., Illian, J. B., Muñoz, F., Bellido, J. M., López-Quílez, A., Conesa, D. (2019) Accounting for preferential sampling in species distribution models Ecology and Evolution, 9, pp. 653-663. (doi: 10.1002/ece3.4789)

Moesta, A., Hours, M.A., Boutigny, L., Davies, V., Kelly, S., Mougeotc, I., Reid, J. (2019) A Weight Loss Diet With Alpha-casozepine and L-tryptophane Improves Health Related Quality of Life in Dogs

Noble, C. E., Wiseman-Orr, L. M., Scott, M. E., Nolan, A. M., Reid, J. (2019) Development, initial validation and reliability testing of a web-based, generic feline health-related quality of life instrument Journal of Feline Medicine and Surgery, 21, pp. 84-94. (doi: 10.1177/1098612X18758176)

Lin, L., Niu, M., Cheung, P., Dunson, D. (2019) Extrinsic Gaussian processes for regression and classification on manifolds Bayesian Analysis, 14, pp. 887-906. (doi: 10.1214/18-BA1135)

Otto, P. (2019) Modeling Spatial Dependence in Local Risks and Uncertainties

Grzegorczyk, M., Aderhold, A., Husmeier, D. (2019) Overview and evaluation of recent methods for statistical inference of gene regulatory networks from time series data Humana Press

Otto, P. (2019) Parallelized Monitoring of Dependent Spatiotemporal Processes

Illian, J. B. (2019) Spatial and spatio-temporal point processes in ecological applications CRC Press

Low, M.I., Bonte, M., Evers, L., Bowman, A.W., Jones, W.R. (2019) Statistical Modelling of Groundwater Contamination Monitoring Data using GWSDAT: a Comparison of Spatial and Spatiotemporal Methods

Lee, D. (2018) A locally adaptive process-convolution model for estimating the health impact of air pollution Annals of Applied Statistics, 12, pp. 2540-2558. (doi: 10.1214/18-AOAS1167)

Krainski, E. T., Gómez-Rubio, V., Bakka, H., Lenzi, A., Castro-Camilo, D., Simpson, D., Lindgren, F., Rue, H. (2018) Advanced Spatial Modeling With Stochastic Partial Differential Equations Using R and INLA Chapman & Hall/CRC

Vittert, L., Katina, S., Ayoub, A., Khambay, B., Bowman, A.W. (2018) Assessing the outcome of orthognathic surgery by three-dimensional soft tissue analysis International Journal of Oral and Maxillofacial Surgery, 47, pp. 1587-1595. (doi: 10.1016/j.ijom.2018.05.024)

Hildeman, A., Bolin, D., Wallin, J., Illian, J. B. (2018) Level set Cox processes Spatial Statistics, 28, pp. 169-193. (doi: 10.1016/j.spasta.2018.03.004)

Richardson, J., Miller, C., Maberly, S., Taylor, P., Globevnik, L., Hunter, P., Jeppesen, E., Mischke, U., Moe, J., Pasztaleniec, A., Søndergaard, M., Carvalho, L. (2018) Effects of multiple stressors on cyanobacteria abundance varies with lake type Global Change Biology, 24, pp. 5044-5055. (doi: 10.1111/gcb.14396)

Caudell, M. A., Mair, C., Subbiah, M., Matthews, L., Quinlan, R. J., Zadoks, R., Keyyu, J., Call, D. R. (2018) Identification of risk factors associated with carriage of resistant Escherichia coli in three culturally diverse ethnic groups in Tanzania: a biological and socioeconomic analysis Lancet Planetary Health, 2, pp. e489-e497. (doi: 10.1016/S2542-5196(18)30225-0)

Browell, J., Drew, D.R., Philippopoulos, K. (2018) Improved very-short-term wind forecasting using atmospheric regimes Wind Energy, 21, pp. 968-979. (doi: 10.1002/we.2207)

Jani, B. D., Nicholl, B. I., McQueenie, R., Connelly, D. T., Hanlon, P., Gallacher, K. I., Lee, D., Mair, F. S. (2018) Multimorbidity and co-morbidity in atrial fibrillation and effects on survival: findings from UK Biobank cohort Europace, 20, pp. f329-f336. (doi: 10.1093/europace/eux322)

Bakka, H., Rue, H., Fuglstad, G.-A., Riebler, A., Bolin, D., Illian, J., Krainski, E., Simpson, D., Lindgren, F. (2018) Spatial modeling with R-INLA: A review Wiley Interdisciplinary Reviews: Computational Statistics, 10, (doi: 10.1002/wics.1443)

Möhrlen, C., Lerner, J., Messner, J. W., Browell, J., Tuohy, A., Zack, J., Collier, C., Giebel, G. (2018) IEA Wind Recommended Practices for the Implementation of Wind Power Forecasting Solutions Part 2 and 3: Designing and Executing Forecasting Benchmarks and Evaluation of Forecast Solutions

Young, D. M., Parry, L. E., Lee, D., Ray, S. (2018) Spatial models with covariates improve estimates of peat depth in blanket peatlands PLoS ONE, 13, (doi: 10.1371/journal.pone.0202691)

Bakka, H. C., Castro-Camilo, D., Franco-Villoria, M., Freni-Sterrantino, A., Huser, T., Rue, H. (2018) Contributed discussion of "Using Stacking to Average Bayesian Predictive Distributions" by Yao et. al​. Bayesian Analysis, 13, pp. 982-985. (doi: 10.1214/17-BA1091)

Hoolohan, C., Larkin, A., McLachlan, C., Falconer, R., Soutar, I., Suckling, J., Varga, L., Haltas, I., Druckman, A., Lumbroso, D., Scott, M., Gilmour, D., Ledbetter, R., McGrane, S., Mitchell, C., Yu, D. (2018) Engaging stakeholders in research to address water–energy–food (WEF) nexus challenges Sustainability Science, 13, pp. 1415-1426. (doi: 10.1007/s11625-018-0552-7)

Gilbert, C., Browell, J., McMillan, D. (2018) A Hierarchical Approach to Probabilistic Wind Power Forecasting (doi: 10.1109/PMAPS.2018.8440571)

Cullen, B., Newby, D., Lee, D., Lyall, D. M., Nevado-Holgado, A. J., Evans, J. J., Pell, J. P., Lovestone, S., Cavanagh, J. (2018) Cross-sectional and longitudinal analyses of outdoor air pollution exposure and cognitive function in UK Biobank Scientific Reports, 8, (doi: 10.1038/s41598-018-30568-6)

Yu, C., Zhang, W., Xu, X., Ji, Y., Yu, S. (2018) Data mining based multi-level aggregate service planning for cloud manufacturing Journal of Intelligent Manufacturing, 29, pp. 1351-1361. (doi: 10.1007/s10845-015-1184-8)

Păun, L. M., Qureshi, M. U., Colebank, M., Hill, N. A., Olufsen, M. S., Haider, M. A., Husmeier, D. (2018) MCMC methods for inference in a mathematical model of pulmonary circulation Statistica Neerlandica, 72, pp. 306-338. (doi: 10.1111/stan.12132)

Giurghita, D., Husmeier, D. (2018) Statistical modelling of cell movement Statistica Neerlandica, 72, pp. 265-280. (doi: 10.1111/stan.12140)

Otto, P., Schmid, W. (2018) Discussion of “Statistical methods for network surveillance” by Daniel Jeske, Nathaniel Stevens, Alexander Tartakovsky, and James Wilson Applied Stochastic Models in Business and Industry, 34, pp. 452-456. (doi: 10.1002/asmb.2360)

Hanlon, P., Nicholl, B. I., Jani, B. D., Lee, D., McQueenie, R., Mair, F. S. (2018) Frailty and pre-frailty in middle-aged and older adults and its association with multimorbidity and mortality: a prospective analysis of 493,737 UK Biobank participants Lancet Public Health, 3, pp. e323-e332. (doi: 10.1016/S2468-2667(18)30091-4)

Elayouty, A., Scott, M., Miller, C., Waldron, S. (2018) Functional Principal Component Analysis for Non-stationary Dynamic Time Series

Wandy, J., Niu, M., Giurghita, D., Daly, R., Rogers, S., Husmeier, D. (2018) ShinyKGode: an interactive application for ODE parameter inference using gradient matching Bioinformatics, 34, pp. 2314-2315. (doi: 10.1093/bioinformatics/bty089)

Gong, M., Miller, C., Scott, M. (2018) Spatio-temporal Modelling of Remote-sensing Lake Surface Water Temperature Data

Wilkie, C., Miller, C., Scott, M., Simis, S., Groom, S., Hunter, P., Spyrakos, E., Tyler, A. (2018) Spatiotemporal Statistical Downscaling for the Fusion of In-lake and Remote Sensing Data

Barra, I., Borowska, A., Koopman, S. J. (2018) Bayesian dynamic modeling of high-frequency integer price changes Journal of Financial Econometrics, 16, pp. 384-424. (doi: 10.1093/jjfinec/nby010)

Browell, J. (2018) Risk constrained trading strategies for stochastic generation with a single-price balancing market Energies, 11, (doi: 10.3390/en11061345)

Reid, J., Wiseman-Orr, L., Scott, M. (2018) Shortening of an existing generic online health-related quality of life instrument for dogs Journal of Small Animal Practice, 59, pp. 334-342. (doi: 10.1111/jsap.12772)

Niu, M., Macdonald, B., Rogers, S., Filippone, M., Husmeier, D. (2018) Statistical inference in mechanistic models: time warping for improved gradient matching Computational Statistics, 33, pp. 1091-1123. (doi: 10.1007/s00180-017-0753-z)

Garthoff, R., Otto, P. (2018) Verfahren zur Überwachung räumlicher autoregressiver Prozesse mit externen Regressoren = Statistical surveillance of spatial autoregressive processes with exogenous regressors AStA Wirtschafts- und Sozialstatistisches Archiv, 12, pp. 107-133. (doi: 10.1007/s11943-018-0224-1)

Bowman, A. W. (2018) Big questions, informative data, excellent science Statistics and Probability Letters, 136, pp. 34-36. (doi: 10.1016/j.spl.2018.02.017)

Chanialidis, C., Evers, L., Neocleous, T., Nobile, A. (2018) Efficient Bayesian inference for COM-Poisson regression models Statistics and Computing, 28, pp. 595-608. (doi: 10.1007/s11222-017-9750-x)

Lindo, A., Zuyev, S., Sagitov, S. (2018) Nonparametric estimation for compound Poisson process via variational analysis on measures Statistics and Computing, 28, pp. 563-577. (doi: 10.1007/s11222-017-9748-4)

Huque, M. H., Anderson, C., Walton, R., Woolford, S., Ryan, L. (2018) Smooth individual level covariates adjustment in disease mapping Biometrical Journal, 60, pp. 597-615. (doi: 10.1002/bimj.201700143)

Scott, E. M. (2018) The role of Statistics in the era of big data: crucial, critical and under-valued Statistics and Probability Letters, 136, pp. 20-24. (doi: 10.1016/j.spl.2018.02.050)

Jones-Todd, C. M., Swallow, B., Illian, J. B., Toms, M. (2018) A spatiotemporal multispecies model of a semicontinuous response Journal of the Royal Statistical Society: Series C (Applied Statistics), 67, pp. 705-722. (doi: 10.1111/rssc.12250)

Mangion, K., Gao, H., Husmeier, D., Luo, X., Berry, C. (2018) Advances in computational modelling for personalised medicine after myocardial infarction Heart, 104, pp. 550-557. (doi: 10.1136/heartjnl-2017-311449)

Lee, D., Rushworth, A., Napier, G. (2018) Spatio-temporal areal unit modelling in R with conditional autoregressive priors using the CARBayesST package Journal of Statistical Software, 84, (doi: 10.18637/jss.v084.i09)

Huang, G., Lee, D., Scott, E. M. (2018) Multivariate space-time modelling of multiple air pollutants and their health effects accounting for exposure uncertainty Statistics in Medicine, 37, pp. 1134-1148. (doi: 10.1002/sim.7570)

Grau-Andres, R., Davies, G. M., Gray, A., Scott, E. M., Waldron, S. (2018) Fire severity is more sensitive to low fuel moisture content on Calluna heathlands than on peat bogs Science of the Total Environment, 616-17, pp. 1261-1269. (doi: 10.1016/j.scitotenv.2017.10.192)

Spyrakos, E., O'Donnell, R., Hunter, P. D., Miller, C., Scott, M., Simis, S. G.H., Neil, C., Barbosa, C. C.F., Binding, C. E., Bradt, S., Bresciani, M., Dall'Olmo, G., Giardino, C., Gitelson, A. A., Kutser, T., Li, L., Matsushita, B., Martinez-Vicente, V., Matthews, M. W., Ogashawara, I., Ruiz-Verdú, A., Schalles, J. F., Tebbs, E., Zhang, Y., Tyler, A. N. (2018) Optical types of inland and coastal waters Limnology and Oceanography, 63, pp. 846-870. (doi: 10.1002/lno.10674)

Castro-Camilo, D., de Carvalho, M., Wadsworth, J. (2018) Time-varying extreme value dependence with application to leading European stock markets Annals of Applied Statistics, 12, pp. 283-309. (doi: 10.1214/17-AOAS1089)

Gallacher, K. I., McQueenie, R., Nicholl, B., Jani, B. D., Lee, D., Mair, F. S. (2018) Risk factors and mortality associated with multimorbidity in people with stroke or transient ischaemic attack: a study of 8,751 UK Biobank participants Journal of Comorbidity, 8, pp. 1-8. (doi: 10.15256/joc.2018.8.129)

Scott, E. M., Naysmith, P., Cook, G. T. (2018) Why do we need 14C inter-comparisons?: The Glasgow 14C inter-comparison series, a reflection over 30 years Quaternary Geochronology, 43, pp. 72-82. (doi: 10.1016/j.quageo.2017.08.001)

Alghamdi, A., Vyshemirsky, V., Birch, D.J.S., Rolinski, O.J. (2018) Detecting beta-amyloid aggregation from the time-resolved emission spectra Methods and Applications in Fluorescence, 6, (doi: 10.1088/2050-6120/aa9f95)

Elliott, A., Leicht, E., Whitmore, A., Reinert, G., Reed-Tsochas, F. (2018) A nonparametric significance test for sampled networks Bioinformatics, 34, pp. 64-71. (doi: 10.1093/bioinformatics/btx419)

Hanlon, P., Nicholl, B. I., Jani, B. D., McQueenie, R., Lee, D., Gallacher, K. I., Mair, F. S. (2018) Examining patterns of multimorbidity, polypharmacy and risk of adverse drug reactions in chronic obstructive pulmonary disease: a cross-sectional UK Biobank study BMJ Open, 8, (doi: 10.1136/bmjopen-2017-018404)

Lindo, A., Sagitov, S. (2018) General linear-fractional branching processes with discrete time Stochastics, 90, pp. 364-378. (doi: 10.1080/17442508.2017.1357722)

Yurk, B. P., Cobbold, C. A. (2018) Homogenization techniques for population dynamics in strongly heterogeneous landscapes Journal of Biological Dynamics, 12, pp. 171-193. (doi: 10.1080/17513758.2017.1410238)

Lazarus, A., Husmeier, D., Papamarkou, T. (2018) Multiphase MCMC sampling for parameter inference in nonlinear ordinary differential equations Proceedings of Machine Learning Research, 84, pp. 1252-1260.

Chung, L. H. C., Birch, D. J.S., Vyshemirsky, V., Ryadnov, M. G., Rolinski, O. J. (2017) Insulin aggregation tracked by its intrinsic TRES Applied Physics Letters, 111, (doi: 10.1063/1.5008477)

McCulloch, R., Cobbold, C. A., Figueiredo, L., Jackson, A., Morrison, L. J., Mugnier, M. R., Papavasiliou, N., Schnaufer, A., Matthews, K. (2017) Emerging challenges in understanding trypanosome antigenic variation Emerging Topics in Life Sciences, 1, pp. 585-592. (doi: 10.1042/ETLS20170104)

Grau-Andrés, R., Davies, G. M., Waldron, S., Scott, E. M., Gray, A. (2017) Leaving moss and litter layers undisturbed reduces the short-term environmental consequences of heathland managed burns Journal of Environmental Management, 204, pp. 102-110. (doi: 10.1016/j.jenvman.2017.08.017)

Yuan, Y., Bachl, F. E., Lindgren, F., Borchers, D. L., Illian, J. B., Buckland, S. T., Rue, H., Gerrodette, T. (2017) Point process models for spatio-temporal distance sampling data from a large-scale survey of blue whales Annals of Applied Statistics, 11, pp. 2270-2297. (doi: 10.1214/17-AOAS1078)

Waddington, J. L., Katina, S., O'Tuathaigh, C. M.P., Bowman, A. W. (2017) Translational genetic modelling of 3D craniofacial dysmorphology: elaborating the facial phenotype of neurodevelopmental disorders through the prism of schizophrenia Current Behavioral Neuroscience Reports, 4, pp. 322-330. (doi: 10.1007/s40473-017-0136-3)

Neslihanoglu, S., Sogiakas, V., McColl, J., Lee, D. (2017) Nonlinearities in the CAPM: evidence from developed and emerging markets Journal of Forecasting, 36, pp. 867-897. (doi: 10.1002/for.2389)

Milotti, E., Vyshemirsky, V., Stella, S., Dogo, F., Chignola, R. (2017) Analysis of the fluctuations of the tumour/host interface Physica A: Statistical Mechanics and its Applications, 486, pp. 587-594. (doi: 10.1016/j.physa.2017.06.005)

Liu, C., Ray, S., Hooker, G. (2017) Functional principal component analysis of spatially correlated data Statistics and Computing, 27, pp. 1639-1654. (doi: 10.1007/s11222-016-9708-4)

Castro-Camilo, D., Lombardo, L., Mai, P. M., Dou, J., Huser, R. (2017) Handling high predictor dimensionality in slope-unit-based landslide susceptibility models through LASSO-penalized Generalized Linear Model Environmental Modelling and Software, 97, pp. 145-156. (doi: 10.1016/j.envsoft.2017.08.003)

Reid, J., Scott, M., Nolan, A. (2017) Pain assessment in companion animals: an update In Practice, 39, pp. 446-451. (doi: 10.1136/inp.j4513)

Gao, H., Mangion, K., Carrick, D., Husmeier, D., Luo, X., Berry, C. (2017) Estimating prognosis in patients with acute myocardial infarction using personalized computational heart models Scientific Reports, 7, (doi: 10.1038/s41598-017-13635-2)

Illian, J. B., Burslem, D. F.R.P. (2017) Improving the usability of spatial point process methodology: an interdisciplinary dialogue between statistics and ecology AStA Advances in Statistical Analysis, 101, pp. 495-520. (doi: 10.1007/s10182-017-0301-8)

Dunbar, E., Naysmith, P., Cook, G.T., Scott, E.M., Xu, S., Tripney, B.G. (2017) Investigation of the analytical F14C bone background value at SUERC Radiocarbon, 59, pp. 1463-1473. (doi: 10.1017/RDC.2017.67)

Dean, N., Pryce, G. (2017) Is the housing market blind to religion? A perceived substitutability approach to homophily and social integration Urban Studies, 54, pp. 3058-3070. (doi: 10.1177/0042098016668779)

Naysmith, P., Dunbar, E., Scott, E.M., Cook, G.T., Tripney, B.G. (2017) Preliminary results for estimating the bone background uncertainties at SUERC using statistical analysis Radiocarbon, 59, pp. 1579-1587. (doi: 10.1017/RDC.2017.70)

Scott, E.M., Naysmith, P., Cook, G.T. (2017) Should archaeologists care about 14C inter-comparisons? Why? A summary report on SIRI Radiocarbon, 59, pp. 1589-1596. (doi: 10.1017/RDC.2017.12)

Lazarus, A., Husmeier, D., Papamarkou, T. (2017) Inference in Complex Systems Using Multi-Phase MCMC Sampling with Gradient Matching

Pasetto, M., Noè, U., Luati, A., Husmeier, D. (2017) Inference on the Duffing System With the Unscented Kalman Filter and Optimization of Sigma Points

Niu, M., Rogers, S., Filippone, M., Husmeier, D. (2017) Parameter Inference in Differential Equation Models Using Time Warped Gradient Matching

Paun, L., Haider, M., Hill, N., Olufsen, M., Qureshi, M., Papamarkou, T., Husmeier, D. (2017) Parameter Inference in the Pulmonary Blood Circulation

Stewart, K., Matthews, L., Scott, E. M., Husmeier, D., Mccowan, C. (2017) Preliminary Investigation of the Influences on Antimicrobial Resistance

Husmeier, D., Ferguson, E., Matthiopoulos, J., Insall, R. (2017) Statistical Inference of the Drivers of Collective Cell Movement

Giurghita, D., Husmeier, D. (2017) Statistical Modelling of Cell Movement Data Using the Unscented Kalman Filter

Castro-Camilo, D., de Carvalho, M. (2017) Spectral density regression for bivariate extremes Stochastic Environmental Research and Risk Assessment, 31, pp. 1603-1613. (doi: 10.1007/s00477-016-1257-z)

Davies, V., Reeve, R., Harvey, W. T., Maree, F. F., Husmeier, D. (2017) A sparse hierarchical Bayesian model for detecting relevant antigenic sites in virus evolution Computational Statistics, 32, pp. 803-843. (doi: 10.1007/s00180-017-0730-6)

Che Roos, N. A., Alsanosi, S. M., Alsieni, M. A., Gupta, M., Padmanabhan, S. (2017) Antihypertensive Drugs and Risk of Cancer: A Systematic Review and Meta-Analysis of 391, 790 Patients (doi: 10.1161/hyp.70.suppl_1.p129)

Bessa, R., Möhrlen, C., Fundel, V., Siefert, M., Browell, J., Haglund El Gaidi, S., Hodge, B.-M., Cali, U., Kariniotakis, G. (2017) Towards improved understanding of the applicability of uncertainty forecasts in the electric power industry Energies, 10, (doi: 10.3390/en10091402)

Malvaldi, A., Weiss, S., Infield, D., Browell, J., Leahy, P., Foley, A.M. (2017) A spatial and temporal correlation analysis of aggregate wind power in an ideally interconnected Europe Wind Energy, 20, pp. 1315-1329. (doi: 10.1002/we.2095)

Barraquand, F., Louca, S., Abbott, K. C., Cobbold, C. A., Cordoleani, F., DeAngelis, D. L., Elderd, B. D., Fox, J. W., Greenwood, P., Hilker, F. M., Murray, D. L., Stieha, C. R., Taylor, R. A., Vitense, K., Wolkowicz, G. S.K., Tyson, R. C. (2017) Moving forward in circles: challenges and opportunities in modelling population cycles Ecology Letters, 20, pp. 1074-1092. (doi: 10.1111/ele.12789)

Ferguson, E. A., Matthiopoulos, J., Insall, R. H., Husmeier, D. (2017) Statistical inference of the mechanisms driving collective cell movement Journal of the Royal Statistical Society: Series C (Applied Statistics), 66, pp. 869-890. (doi: 10.1111/rssc.12203)

Browell, J., Gilbert, C. (2017) Cluster-based Regime-switching AR for the EEM 2017 Wind Power Forecasting Competition (doi: 10.1109/EEM.2017.7982034)

Alexander, C., Stuart-Smith, J., Neocleous, T., Evers, L. (2017) Using Chain Graph Models for Structural Inference With an Application to Linguistic Data

Otto, P. (2017) A note on efficient simulation of multidimensional spatial autoregressive processes Communications in Statistics: Simulation and Computation, 46, pp. 4547-4558. (doi: 10.1080/03610918.2015.1122050)

Ferguson, E. A., Matthiopoulos, J., Husmeier, D. (2017) Constructing Wildebeest Density Distributions by Spatio-temporal Smoothing of Ordinal Categorical Data Using GAMs

Lazarus, A., Husmeier, D., Papamarkou, T. (2017) Inference in Complex Systems Using Multi-Phase MCMC Sampling With Gradient Matching Burn-in

Paun, L. M., Qureshi, M. U., Colebank, M., Haider, M. A., Olufsen, M. S., Hill, N. A., Husmeier, D. (2017) Parameter Inference in the Pulmonary Circulation of Mice

Pasetto, M. E., Husmeier, D., Noè, U., Luati, A. (2017) Statistical Inference in the Duffing System with the Unscented Kalman Filter

Giurghita, D., Husmeier, D. (2017) Statistical Modelling of Cell Movement

Aderhold, A., Husmeier, D., Grzegorczyk, M. (2017) Approximate Bayesian inference in semi-mechanistic models Statistics and Computing, 27, pp. 1003-1040. (doi: 10.1007/s11222-016-9668-8)

Gao, H., Aderhold, A., Mangion, K., Luo, X., Husmeier, D., Berry, C. (2017) Changes and classification in myocardial contractile function in the left ventricle following acute myocardial infarction Journal of the Royal Society: Interface, 14, (doi: 10.1098/rsif.2017.0203)

Bush, A., Rahel, S., Wilting, A., Kristine, B., Cole, B., Balzter, H., Martius, C., Zlinszky, A., Calvignac-Spencer, S., Cobbold, C. A., Dawson, T. P., Emerson, B. C., Ferrier, S., Gilbert, M. T. P., Herold, M., Jones, L., Leendertz, F. H., Matthews, L., Millington, J. D.A., Olson, J. R., Ovaskainen, O., Raffaelli, D., Reeve, R., Rödel, M.-O., Rodgers, T. W., Snape, S., Visseren-Hamakers, I., Wogler, A. P., White, P. C.L., Wooster, M. J., Yu, D. W. (2017) Connecting Earth observation to high-throughput biodiversity data Nature Ecology and Evolution, 1, (doi: 10.1038/s41559-017-0176)

Grzegorczyk, M., Aderhold, A., Husmeier, D. (2017) Targeting Bayes factors with direct-path non-equilibrium thermodynamic integration Computational Statistics, 32, pp. 717-761. (doi: 10.1007/s00180-017-0721-7)

Reid, J., Scott, E.M., Calvo, G., Nolan, A.M. (2017) Definitive Glasgow Acute Pain Scale for Cats: validation and intervention level Veterinary Record, 108, (doi: 10.1136/vr.104208)

Yamaoka, T. T., Flaherty, D., Pawson, P., Scott, M., Auckburally, A. (2017) Comparison of arterial blood pressure measurements obtained invasively or oscillometrically using a Datex S/5 Compact monitor in anaesthetised adult horses Veterinary Anaesthesia and Analgesia, 44, pp. 492-501. (doi: 10.1016/j.vaa.2016.05.008)

Olivieri, A., Sidore, C., Achilli, A., Angius, A., Posth, C., Furtwängler, A., Brandini, S., Capodiferro, M. R., Gandini, F., Zoledziewska, M., Pitzalis, M., Maschio, A., Busonero, F., Lai, L., Skeates, R., Gradoli, M. G., Beckett, J., Marongiu, M., Mazzarello, V., Marongiu, P., Rubino, S., Rito, T., Macaulay, V., Semino, O., Pala, M., Abecasis, G. R., Schlessinger, D., Conde-Sousa, E., Soares, P., Richards, M. B., Cucca, F., Torroni, A. (2017) Mitogenome diversity in Sardinians: a genetic window onto an island's past Molecular Biology and Evolution, 34, pp. 1230-1239. (doi: 10.1093/molbev/msx082)

Papáček, Š., Matonoha, C., Macdonald, B. (2017) Closed-form formulae vs. PDE based numerical solution for the FRAP data processing: Theoretical and practical comparison Computers and Mathematics with Applications, 73, pp. 1673-1683. (doi: 10.1016/j.camwa.2017.02.010)

Lee, D., Mukhopadhyay, S., Rushworth, A., Sahu, S. K. (2017) A rigorous statistical framework for spatio-temporal pollution prediction and estimation of its long-term impact on health Biostatistics, 18, pp. 370-385. (doi: 10.1093/biostatistics/kxw048)

Cavalcante, L., Bessa, R. J., Reis, M., Browell, J. (2017) LASSO vector autoregression structures for very short-term wind power forecasting Wind Energy, 20, pp. 657-675. (doi: 10.1002/we.2029)

Labrosse, N., Bownes, J., Forrest, D., MacTaggart, D., McGookin, E., Poet, R., Ray, S., Fischbacher-Smith, M., Jackson, M., McEwan, M., Pringle Barnes, G., Sheridan, N. (2017) Preparing for the Journey: Supporting Students to Make Successful Transitions Into and Out of Taught Postgraduate Study

Pannullo, F., Lee, D., Neal, L., Dalvi, M., Agnew, P., O'Connor, F. M., Mukhopadhyay, S., Sahu, S., Sarran, C. (2017) Quantifying the impact of current and future concentrations of air pollutants on respiratory disease risk in England Environmental Health, 16, (doi: 10.1186/s12940-017-0237-1)

Rue, H., Riebler, A., Sørbye, S. H., Illian, J. B., Simpson, D. P., Lindgren, F. K. (2017) Bayesian computing with INLA: a review Annual Review of Statistics and Its Application, 4, pp. 395-421. (doi: 10.1146/annurev-statistics-060116-054045)

Gallacher, K., Miller, C., Scott, E.M., Willows, R., Pope, L., Douglass, J. (2017) Flow-directed PCA for monitoring networks Environmetrics, 28, (doi: 10.1002/env.2434)

Anderson, C., Ryan, L. (2017) A comparison of spatio-temporal disease mapping approaches including an application to ischaemic heart disease in New South Wales, Australia International Journal of Environmental Research and Public Health, 14, (doi: 10.3390/ijerph14020146)

Otto, P., Lange, A.-L. (2017) Arbeitsbuch der Angewandten Statistik: Mit Aufgaben zur Software R und detaillierten Lösungen Springer Gabler

Rushworth, A., Lee, D., Sarran, C. (2017) An adaptive spatio-temporal smoothing model for estimating trends and step changes in disease risk Journal of the Royal Statistical Society: Series C (Applied Statistics), 66, pp. 141-157. (doi: 10.1111/rssc.12155)

Anderson, C., Lee, D., Dean, N. (2017) Spatial clustering of average risks and risk trends in Bayesian disease mapping Biometrical Journal, 59, pp. 41-56. (doi: 10.1002/bimj.201600018)

Millar, K., Bowman, A. W. (2017) “Hartnell's time machine” reprise: Further implications of zinc, lead and copper in the thumbnail of a Franklin expedition crewmember Journal of Archaeological Science: Reports, 13, pp. 286-290. (doi: 10.1016/j.jasrep.2017.03.046)

Lawson, A., Lee, D. (2017) Bayesian disease mapping for public health Elsevier

Liu, Z., Macdonald, B., Husmeier, D., Giurghita, D. (2017) Estimating Parameters of Partial Differential Equations with Gradient Matching

Python, A., Illian, J., Jones-Todd, C., Blangiardo, M. (2017) Explaining the lethality of Boko Haram’s terrorist attacks in Nigeria, 2009–2014: a hierarchical Bayesian approach Springer

Noè, U., Chen, W. W., Filippone, M., Hill, N., Husmeier, D. (2017) Inference in a Partial Differential Equations Model of Pulmonary Arterial and Venous Blood Circulation using Statistical Emulation (doi: 10.1007/978-3-319-67834-4_15)

McMillan, D., Browell, J. (2017) Optimisation of Wind Energy O&M Decision Making Under Uncertainty [Final Report]: Exploitation Plan

Niu, M., Rogers, S., Filippone, M., Husmeier, D. (2017) Parameter Inference in Differential Equation Models of Biopathways using Time Warped Gradient Matching (doi: 10.1007/978-3-319-67834-4_12)

Browell, J., Gilbert, C., McMillan, D. (2017) Use of Turbine-level Data for Improved Wind Power Forecasting (doi: 10.1109/PTC.2017.7981134)

Ledo, A., Cornulier, T., Illian, J. B., Iida, Y., Kassim, A. R., Burslem, D. F. R. P. (2016) Re-evaluation of individual diameter: height allometric models to improve biomass estimation of tropical trees Ecological Applications, 26, pp. 2376-2382. (doi: 10.1002/eap.1450)

Ventrucci, M., Cocchi, D., Scott, E. M. (2016) Smoothing of land use maps for trend and change detection in urbanization Evironmental and Ecological Statistics, 23, pp. 565-584. (doi: 10.1007/s10651-016-0354-y)

Dowell, J., Hawker, G., Bell, K., Gill, S. (2016) A Review of Probabilistic Methods for Defining Reserve Requirements (doi: 10.1109/PESGM.2016.7741361)

Ledo, A., Illian, J. B., Schnitzer, S. A., Wright, S. J., Dalling, J. W., Burslem, D. F. R. P., Zotz, G. (2016) Lianas and soil nutrients predict fine-scale distribution of above-ground biomass in a tropical moist forest Journal of Ecology, 104, pp. 1819-1828. (doi: 10.1111/1365-2745.12635)

Ferguson, E. A., Matthiopoulos, J., Insall, R. H., Husmeier, D. (2016) Inference of the drivers of collective movement in two cell types: Dictyostelium and melanoma Journal of the Royal Society: Interface, 13, (doi: 10.1098/rsif.2016.0695)

Otto, P., Schmid, W. (2016) Spatiotemporal analysis of German real-estate prices Annals of Regional Science, 60, pp. 41-72. (doi: 10.1007/s00168-016-0789-y)

Lee, D., Lawson, A. (2016) Quantifying the spatial inequality and temporal trends in maternal smoking rates in Glasgow Annals of Applied Statistics, 10, pp. 1427-1446. (doi: 10.1214/16-AOAS941)

Sagitov, S., Lindo, A. (2016) A special family of Galton-Watson processes with explosions Springer

Minghella, E., Auckburally, A., Pawson, P., Scott, M. E., Flaherty, D. (2016) Clinical effects of midazolam or lidocaine co-induction with a propofol target-controlled infusion (TCI) in dogs Veterinary Anaesthesia and Analgesia, 43, pp. 472-481. (doi: 10.1111/vaa.12336)

Otto, P. (2016) Detection of spatial change points in the mean and covariances of multivariate simultaneous autoregressive models Biometrical Journal, 58, pp. 1113-1137. (doi: 10.1002/bimj.201500148)

Browell, J., Dinwoodie, I., McMillan, D. (2016) Forecasting for Day-ahead Offshore Maintenance Scheduling Under Uncertainty (doi: 10.1201/9781315374987-16)

Martyna, A., Zadora, G., Neocleous, T., Michalska, A., Dean, N. (2016) Hybrid approach combining chemometrics and likelihood ratio framework for reporting the evidential value of spectra Analytica Chimica Acta, 931, pp. 34-46. (doi: 10.1016/j.aca.2016.05.016)

Giurghita, D., Husmeier, D. (2016) Inference in Nonlinear Systems with Unscented Kalman Filters

Mavrogonatou, L., Vyshemirsky, V. (2016) Sequential Importance Sampling for Online Bayesian Changepoint Detection

Napier, G., Lee, D., Robertson, C., Lawson, A., Pollock, K. G. (2016) A model to estimate the impact of changes in MMR vaccine uptake on inequalities in measles susceptibility in Scotland Statistical Methods in Medical Research, 25, pp. 1185-1200. (doi: 10.1177/0962280216660420)

Lawson, A. B., Lee, D., MacNab, Y. (2016) Editorial Statistical Methods in Medical Research, 25, pp. 1079. (doi: 10.1177/0962280216660410)

Pannullo, F., Lee, D., Waclawski, E., Leyland, A. H. (2016) How robust are the estimated effects of air pollution on health? Accounting for model uncertainty using Bayesian model averaging Spatial and Spatio-Temporal Epidemiology, 18, pp. 53-62. (doi: 10.1016/j.sste.2016.04.001)

Huque, M. H., Anderson, C., Walton, R., Ryan, L. (2016) Individual level covariate adjusted conditional autoregressive (indiCAR) model for disease mapping International Journal of Health Geographics, 15, (doi: 10.1186/s12942-016-0055-7)

Garthoff, R., Otto, P. (2016) Control charts for multivariate spatial autoregressive models AStA Advances in Statistical Analysis, 101, pp. 67-94. (doi: 10.1007/s10182-016-0276-x)

Ewing, D. A., Cobbold, C. A., Nunn, M. A., Purse, B. V., White, S. M. (2016) Modelling the effect of temperature on the seasonal population dynamics of temperate mosquitoes Journal of Theoretical Biology, 400, pp. 65-79. (doi: 10.1016/j.jtbi.2016.04.008)

Macdonald, B., Niu, M., Rogers, S., Filippone, M., Husmeier, D. (2016) Approximate parameter inference in systems biology using gradient matching: a comparative evaluation BioMedical Engineering OnLine, 15, (doi: 10.1186/s12938-016-0186-x)

Bessa, R. J., Dowell, J., Pinson, P. (2016) Renewable energy forecasting John Wiley and Sons Ltd

Millar, K., Bowman, A. W., Battersby, W., Welbury, R. R. (2016) The health of nine Royal Naval Arctic crews, 1848 to 1854: implications for the lost Franklin Expedition Polar Record, 52, pp. 423-441. (doi: 10.1017/S0032247416000176)

Browell, J. (2016) Forecasting Electricity Prices and Market Length for Trading Stochastic Generation in Markets With a Single-price Balancing Mechanism

Niu, M., Rogers, S., Filippone, M., Husmeier, D. (2016) Fast inference in nonlinear dynamical systems using gradient matching Proceedings of Machine Learning Research, 48, pp. 1699-1707.

Niu, M., Blackwell, P. G., Skarin, A. (2016) Modeling interdependent animal movement in continuous time Biometrics, 72, pp. 315-324. (doi: 10.1111/biom.12454)

Rolinski, O. J., McLaughlin, D., Birch, D. J.S., Vyshemirsky, V. (2016) Resolving environmental microheterogeneity and dielectric relaxation in fluorescence kinetics of protein Methods and Applications in Fluorescence, 4, (doi: 10.1088/2050-6120/4/2/024001)

Flynt, A., Dean, N. (2016) A survey of popular R packages for cluster analysis Journal of Educational and Behavioral Statistics, 41, pp. 205-225. (doi: 10.3102/1076998616631743)

Cai, X., Li, Z., Scott, E. M., Li, X., Tang, M. (2016) Short-term effects of atmospheric particulate matter on myocardial infarction: a cumulative meta-analysis Environmental Science and Pollution Research, 7, pp. 6139-6148. (doi: 10.1007/s11356-016-6186-3)

Aderhold, A., Smith, V. A., Husmeier, D. (2016) Biological network inference at multiple scales: from gene regulation to species interactions John Wiley & Sons

Elayouty, A., Scott, M., Miller, C., Waldron, S., Franco-Villoria, M. (2016) Challenges in modeling detailed and complex environmental data sets: a case study modeling the excess partial pressure of fluvial CO2 Evironmental and Ecological Statistics, 23, pp. 65-87. (doi: 10.1007/s10651-015-0329-4)

Simpson, D., Illian, J.B., Lindgren, F., Sørbye, S.H., Rue, H. (2016) Going off grid: computationally efficient inference for log-Gaussian Cox processes Biometrika, 103, pp. 49-70. (doi: 10.1093/biomet/asv064)

Soares, P. J., Trejaut, J. A., Rito, T., Cavadas, B., Hill, C., Eng, K. K., Mormina, M., Brandao, A., Fraser, R. M., Wang, T.-Y., Loo, J.-H., Snell, C., Ko, T.-M., Amorim, A., Pala, M., Macaulay, V., Bulbeck, D., Wilson, J. F., Gusmao, L., Pereira, L., Oppenheimer, S., Lin, M., Richards, M. B. (2016) Resolving the ancestry of Austronesian-speaking populations Human Genetics, 135, pp. 309-326. (doi: 10.1007/s00439-015-1620-z)

Katina, S., McNeil, K., Ayoub, A., Guilfoyle, B., Khambay, B., Siebert, J., Sukno, F., Rojas, M., Vittert, L., Waddington, J., Whelan, P. F., Bowman, A. (2016) The definitions of three-dimensional landmarks on the human face: an interdisciplinary view Journal of Anatomy, 228, pp. 355-365. (doi: 10.1111/joa.12407)

Dowell, J., Pinson, P. (2016) Very-short-term probabilistic wind power forecasts by sparse vector autoregression IEEE Transactions on Smart Grid, 7, pp. 763-770. (doi: 10.1109/TSG.2015.2424078)

Altieri, L., Cocchi, D., Greco, F., Illian, J.B., Scott, E.M. (2016) Bayesian P-splines and advanced computing in R for a changepoint analysis on spatio-temporal point processes Journal of Statistical Computation and Simulation, 86, pp. 2531-2545. (doi: 10.1080/00949655.2016.1146280)

Catterson, V.M., McMillan, D., Dinwoodie, I., Revie, M., Dowell, J., Quigley, J., Wilson, K. (2016) An economic impact metric for evaluating wave height forecasters for offshore wind maintenance access Wind Energy, 19, pp. 199-212. (doi: 10.1002/we.1826)

Anderson, C., Lee, D., Dean, N. (2016) Bayesian cluster detection via adjacency modelling Spatial and Spatio-Temporal Epidemiology, 16, pp. 11-20. (doi: 10.1016/j.sste.2015.11.005)

Blackwell, P. G., Niu, M., Lambert, M. S., LaPoint, S. D., O'Hara, R. B. (2016) Exact Bayesian inference for animal movement in continuous time Methods in Ecology and Evolution, 7, pp. 184-195. (doi: 10.1111/2041-210X.12460)

Brown, C., Illian, J. B., Burslem, D. F. R. P., Sandhu, L. (2016) Success of spatial statistics in determining underlying process in simulated plant communities Journal of Ecology, 104, pp. 160-172. (doi: 10.1111/1365-2745.12493)

Lee, D., Sahu, S. (2016) Estimating the health impact of air pollution fields CRC

Chignola, R., Sega, M., Stella, S., Vyshemirsky, V., Milotti, E. (2016) From single-cell dynamics to scaling laws in oncology World Scientific

Reeve, R., Leinster, T., Cobbold, C. A., Thompson, J., Brummitt, N., Mitchell, S. N., Matthews, L. (2016) How to partition diversity arXiv,

Kavanagh, L., Lee, D., Pryce, G. (2016) Is poverty decentralizing? Quantifying uncertainty in the decentralization of urban poverty Annals of the American Association of Geographers, 106, pp. 1286-1298. (doi: 10.1080/24694452.2016.1213156)

Davies, V., Reeve, R., Harvey, W. T., Husmeier, D. (2016) Selecting random effect components in a sparse hierarchical Bayesian model for identifying antigenic variability Springer

Lindo, A., Sagitov, S. (2015) Asymptotic results for the number of Wagner’s solutions to a generalised birthday problem Statistics and Probability Letters, 107, pp. 356-361. (doi: 10.1016/j.spl.2015.09.014)

Cobbold, C. A., Lutscher, F., Sherratt, J. A. (2015) Diffusion-driven instabilities and emerging spatial patterns in patchy landscapes Ecological Complexity, 24, pp. 69-81. (doi: 10.1016/j.ecocom.2015.10.001)

Malvaldi, A., Dowell, J., Weiss, S., Infield, D. (2015) Wind Prediction Enhancement by Exploiting Data Non-stationarity (doi: 10.1049/cp.2015.1795)

Macdonald, B., Husmeier, D. (2015) Gradient matching methods for computational inference in mechanistic models for systems biology: a review and comparative analysis Frontiers in Bioengineering and Biotechnology, 3, (doi: 10.3389/fbioe.2015.00180)

Altieri, L., Scott, E. M., Cocchi, D., Illian, J. B. (2015) A changepoint analysis of spatio-temporal point processes Spatial Statistics, 14, pp. 197-207. (doi: 10.1016/j.spasta.2015.05.005)

Dunlop, K.M., Ruxton, G.D., Scott, E.M., Bailey, D.M. (2015) Absolute abundance estimates from shallow water baited underwater camera surveys; a stochastic modelling approach tested against field data Journal of Experimental Marine Biology and Ecology, 472, pp. 126-134. (doi: 10.1016/j.jembe.2015.07.010)

Lee, D., Sarran, C. (2015) Controlling for unmeasured confounding and spatial misalignment in long-term air pollution and health studies Environmetrics, 26, pp. 477-487. (doi: 10.1002/env.2348)

Fitzer, S. C., Vittert, L., Bowman, A., Kamenos, N. A., Phoenix, V. R., Cusack, M. (2015) Ocean acidification and temperature increase impacts mussel shell shape and thickness: problematic for protection? Ecology and Evolution, 5, pp. 4875-4884. (doi: 10.1002/ece3.1756)

Russell, N., Cook, G. T., Ascough, P. L., Scott, E. M. (2015) A period of calm in Scottish seas: a comprehensive study of ΔR values for the northern British Isles coast and the consequent implications for archaeology and oceanography Quaternary Geochronology, 30, pp. 34-41. (doi: 10.1016/j.quageo.2015.08.001)

Huang, G., Lee, D., Scott, M. (2015) An integrated Bayesian model for estimating the long-term health effects of air pollution by fusing modelled and measured pollution data: a case study of nitrogen dioxide concentrations in Scotland Spatial and Spatio-Temporal Epidemiology, 14-15, pp. 63-74. (doi: 10.1016/j.sste.2015.09.002)

Pannullo, F., Lee, D., Waclawski, E., Leyland, A. H. (2015) Improving spatial nitrogen dioxide prediction using diffusion tubes: a case study in West Central Scotland Atmospheric Environment, 118, pp. 227-235. (doi: 10.1016/j.atmosenv.2015.08.009)

Dunlop, K. M., Scott, E. M., Parsons, D., Bailey, D. M. (2015) Do agonistic behaviours bias baited remote underwater video surveys of fish? Marine Ecology, 36, pp. 810-818. (doi: 10.1111/maec.12185)

Evers, L., Molinari, D.A., Bowman, A.W., Jones, W.R., Spence, M.J. (2015) Efficient and automatic methods for flexible regression on spatiotemporal data, with applications to groundwater monitoring Environmetrics, 26, pp. 431-441. (doi: 10.1002/env.2347)

Nightingale, G. F., Illian, J. B., King, R. (2015) Pairwise interaction point processes for modelling bivariate spatial point patterns in the presence of interaction uncertainty Journal of Environmental Statistics, 7,

Napier, G., Nobile, A., Neocleous, T. (2015) An online application for the classification and evidence evaluation of forensic glass fragments Chemometrics and Intelligent Laboratory Systems, 146, pp. 418-425. (doi: 10.1016/j.chemolab.2015.06.013)

Rolinski, O. J., Wellbrock, T., Birch, D. J.S., Vyshemirsky, V. (2015) Tyrosine photophysics during the early stages of β-amyloid aggregation leading to Alzheimer’s Journal of Physical Chemistry Letters, 6, pp. 3116-3120. (doi: 10.1021/acs.jpclett.5b01285)

Ponomarev, D., Miller, C., Govan, L., Haig, C., Wu, O., Langhorne, P. (2015) Complications following incident stroke resulting in readmissions: an analysis of data from three Scottish health surveys International Journal of Stroke, 10, pp. 911-917. (doi: 10.1111/ijs.12191)

Cobbold, C. A., Teng, J., Muldowney, J. S. (2015) The influence of host competition and predation on tick densities and management implications Theoretical Ecology, 8, pp. 349-368. (doi: 10.1007/s12080-015-0255-y)

Rushworth, A.M., Peterson, E.E., Ver Hoef, J.M., Bowman, A.W. (2015) Validation and comparison of geostatistical and spline models for spatial stream networks Environmetrics, 25, pp. 327-338. (doi: 10.1002/env.2340)

O'Donnell, R., Miller, C., Scott, E. (2015) Within Lake Clustering of High Resolution Satellite Retrievals: A Functional Data and Clustering Approach

Macdonald, B., Higham, C., Husmeier, D. (2015) Controversy in mechanistic modelling with Gaussian processes Proceedings of Machine Learning Research, 37, pp. 1539-1547.

Noè, U., Filippone, M., Husmeier, D. (2015) Emulation of ODEs with Gaussian Processes

Niu, M., Filippone, M., Husmeier, D., Rogers, S. (2015) Inference in Nonlinear Differential Equations

Grzegorczyk, M., Aderhold, A., Husmeier, D. (2015) Network Reconstruction with Realistic Models

Wilkie, C. J., Scott, E. M., Miller, C., Tyler, A. N., Hunter, P. D., Spyrakos, E. (2015) Data Fusion of Remote-sensing and In-lake chlorophylla Data Using Statistical Downscaling (doi: 10.1016/j.proenv.2015.05.014)

Gong, M., Miller, C., Scott, E. (2015) Functional PCA for Remotely Sensed Lake Surface Water Temperature Data (doi: 10.1016/j.proenv.2015.05.015)

Bowman, A. W., Katina, S., Smith, J., Brown, D. (2015) Anatomical curve identification Computational Statistics and Data Analysis, 86, pp. 52-64. (doi: 10.1016/j.csda.2014.12.007)

Millar, K., Bowman, A. W., Battersby, W. (2015) A re-analysis of the supposed role of lead poisoning in Sir John Franklin’s last expedition, 1845-1848 Polar Record, 51, pp. 224-238. (doi: 10.1017/S0032247413000867)

Mair, C., Matthews, L., Prada J. de Cisneros, J., Stefan, T., Stear, M. J. (2015) Multitrait indices to predict worm length and number in sheep with natural, mixed predominantly Teladorsagia circumcincta infection Parasitology, 142, pp. 773-782. (doi: 10.1017/S0031182014001905)

Hughes, J. S., Cobbold, C. A., Haynes, K., Dwyer, G. (2015) The effects of forest spatial structure on insect outbreak dynamics: insights from host-parasitoid models American Naturalist, 183, pp. E130-E152. (doi: 10.1086/680860)

Bagchi, R., Illian, J. B., Murrell, D. (2015) A method for analysing replicated point patterns in ecology Methods in Ecology and Evolution, 6, pp. 482-490. (doi: 10.1111/2041-210X.12335)

Cook, G.T., Ascough, P.L., Bonsall, C., Hamilton, W.D., Russell, N., Sayle, K.L., Scott, E.M., Bownes, J.M. (2015) Best practice methodology for 14C calibration of marine and mixed terrestrial/marine samples Quaternary Geochronology, 27, pp. 164-171. (doi: 10.1016/j.quageo.2015.02.024)

Macdonald, B., Husmeier, D. (2015) Computational inference in systems biology Springer

Grzegorczyk, M., Aderhold, A., Husmeier, D. (2015) Inferring bi-directional interactions between circadian clock genes and metabolism with model ensembles Statistical Applications in Genetics and Molecular Biology, 14, pp. 143-167. (doi: 10.1515/sagmb-2014-0041)

O'Donnell, R.A., Miller, C.A., Scott, E.M. (2015) Spatially weighted functional clustering of river network data Journal of the Royal Statistical Society: Series C (Applied Statistics), 64, pp. 491-506. (doi: 10.1111/rssc.12082)

Moser, C. B., Gupta, M., Archer, B. N., White, L. F. (2015) The impact of prior information on estimates of disease transmissibility using Bayesian tools PLoS ONE, 10, (doi: 10.1371/journal.pone.0118762)

Prasad, S., Katina, S., Hennessy, R. J., Murphy, K. C., Bowman, A. W., Waddington, J. L. (2015) Craniofacial dysmorphology in 22q11.2 deletion syndrome by 3D laser surface imaging and geometric morphometrics: illuminating the developmental relationship to risk for psychosis American Journal of Medical Genetics Part A, 167, pp. 529-536. (doi: 10.1002/ajmg.a.36893)

Finazzi, F., Haggarty, R., Miller, C., Scott, M., Fassò, A. (2015) A comparison of clustering approaches for the study of the temporal coherence of multiple time series Stochastic Environmental Research and Risk Assessment, 29, pp. 463-475. (doi: 10.1007/s00477-014-0931-2)

Napier, G., Neocleous, T., Nobile, A. (2015) A composite Bayesian hierarchical model of compositional data with zeros Journal of Chemometrics, 9, pp. 96-108. (doi: 10.1002/cem.2681)

Lee, D., Minton, J., Pryce, G. (2015) Bayesian inference for the dissimilarity index in the presence of spatial autocorrelation Spatial Statistics, 11, pp. 81-95. (doi: 10.1016/j.spasta.2014.12.001)

Jull, A.J.T., Scott, E.M., Bierman, P. (2015) The CRONUS-Earth inter-comparison for cosmogenic isotope analysis Quaternary Geochronology, 26, pp. 3-10. (doi: 10.1016/j.quageo.2013.09.003)

Mair, C., Stear, M., Johnson, P., Denwood, M., Jimenez de Cisneros, J. P., Stefan, T., Matthews, L. (2015) A Bayesian generalized random regression model for estimating heritability using overdispersed count data Genetics Selection Evolution, 47, (doi: 10.1186/s12711-015-0125-5)

Reid, J., Wiseman-Orr, M. L., Nolan, A., Scott, E. M. (2015) Health-related quality of life measurement Elsevier

Higham, C. F., Husmeier, D. (2015) Inference of circadian regulatory pathways based on delay differential equations Springer

Dowell, J., Weiss, S., Infield, D. (2015) Kernel Methods for Short-term Spatio-temporal Wind Prediction (doi: 10.1109/PESGM.2015.7285965)

Smith, E., Miller, C., McConway, K., Merrill, S., Opsomer, J., Zacks, S., Sloan, R., House, L. (2015) Statistics for the Curious: Why Study Statistics? Curious Academic Publishing

Heydtmann, M., Macdonald, B., Lewsey, J., Masson, N., Cunningham, L., Irnazarow, A., Nardone, A., Cosgrave, J., Chick, J. (2015) Tailored dose baclofen in patients with alcoholic liver disease: a case series with 2-year follow-up of hospitalisation Addiction Research and Theory, 23, pp. 510-517. (doi: 10.3109/16066359.2015.1040003)

Calvo, G., Holden, E., Reid, J., Scott, E.M., Firth, A., Bell, A., Robertson, S., Nolan, A.M. (2014) Development of a behaviour-based measurement tool with defined intervention level for assessing acute pain in cats Journal of Small Animal Practice, 55, pp. 622-629. (doi: 10.1111/jsap.12280)

Holden, E., Calvo, G., Collins, M., Bell, A., Reid, J., Scott, E.M., Nolan, A.M. (2014) Evaluation of facial expression in acute pain in cats Journal of Small Animal Practice, 55, pp. 615-621. (doi: 10.1111/jsap.12283)

Rolinski, O. J., Vyshemirsky, V. (2014) Fluorescence kinetics of tryptophan in a heterogeneous environment Methods and Applications in Fluorescence, 2, (doi: 10.1088/2050-6120/2/4/045002)

Cheng, Y., Ray, S. (2014) Parallel and hierarchical mode association clustering with an R package Modalclust Open Journal of Statistics, 4, pp. 826-836. (doi: 10.4236/ojs.2014.410078)

Dowell, J., Weiss, S., Hill, D., Infield, D. (2014) Short-term spatio-temporal prediction of wind speed and direction Wind Energy, 17, pp. 1945-1955. (doi: 10.1002/we.1682)

Moodie, E. E.M., Dean, N., Sun, Y. R. (2014) Q-learning: flexible learning about useful utilities Statistics in Biosciences, 6, pp. 223-243. (doi: 10.1007/s12561-013-9103-z)

Prada Jimenez de Cisneros, J., Stear, M. J., Mair, C., Singleton, D., Stefan, T., Stear, A., Marion, G., Matthews, L. (2014) An explicit immunogenetic model of gastrointestinal nematode infection in sheep Journal of the Royal Society: Interface, 11, pp. 20140416-20140416. (doi: 10.1098/rsif.2014.0416)

Ventrucci, M., Bowman, A. W., Miller, C., Gross, J. (2014) Quasi-periodic spatiotemporal models of brain activation in single-trial MEG experiments Statistical Modelling, 14, pp. 417-437. (doi: 10.1177/1471082X14524673)

Mas, I., Elliott, A. (2014) Where's the Cash? The Geography of Cash Points in Tanzania

Malvaldi, A., Dowell, J., Weiss, S., Infield, D., Hill, D. (2014) Wind Prediction Enhancement by Supplementing Measurements with Numerical Weather Prediction Now-Casts

Lee, D., Minton, J., Pryce, G. (2014) Inference for segregation indices in the presence of spatial autocorrelation

Livingston, M., Lee, D. (2014) "The Glasgow effect?"– the result of the geographical patterning of deprived areas? Health and Place, 29, pp. 1-9. (doi: 10.1016/j.healthplace.2014.05.002)

Chignola, R., Sega, M., Stella, S., Vyshemirsky, V., Milotti, E. (2014) From single-cell dynamics to scaling laws in oncology Biophysical Reviews and Letters, 9, pp. 273-284. (doi: 10.1142/S1793048014300035)

Cheng, Y., Ray, S. (2014) Multivariate modality inference using Gaussian kernel Open Journal of Statistics, 4, pp. 419-434. (doi: 10.4236/ojs.2014.45041)

Rushworth, A., Lee, D., Mitchell, R. (2014) A spatio-temporal model for estimating the long-term effects of air pollution on respiratory hospital admissions in Greater London Spatial and Spatio-Temporal Epidemiology, 10, pp. 29-38. (doi: 10.1016/j.sste.2014.05.001)

Anderson, C., Lee, D., Dean, N. (2014) Identifying clusters in Bayesian disease mapping Biostatistics, 15, pp. 457-469. (doi: 10.1093/biostatistics/kxu005)

McDonald, E., Watterson, A., Tyler, A. N., McArthur, J., Scott, E. M. (2014) Multi-factorial influences on sex ratio: a spatio-temporal investigation of endocrine disruptor pollution and neighborhood stress International Journal of Occupational and Environmental Health, 20, pp. 235-246. (doi: 10.1179/2049396714Y.0000000073)

Bell, A., Lo, T.-W. R., Brown, D., Bowman, A. W., Siebert, J. P., Simmons, D. R., Millett, D. T., Ayoub, A. F. (2014) Three-dimensional assessment of facial appearance following surgical repair of unilateral cleft lip and palate Cleft Palate: Craniofacial Journal, 51, pp. 462-471. (doi: 10.1597/12-140)

Elayouty, A., Scott, E., Miller, C., Waldron, S., Franco-Villoria, M. (2014) Visualisation and Modelling of Environmental Sensor Time Series

Bis, J. C., DeStefano, A., Liu, X., Brody, J. A., Choi, S. H., Verhaaren, B. F. J., Debette, S., Ikram, M. A., Shahar, E., Butler, K. R., Gottesman, R. F., Muzny, D., Kovar, C. L., Psaty, B. M., Hofman, A., Lumley, T., Gupta, M., Wolf, P. A., van Duijn, C., Gibbs, R. A., Mosley, T. H., Longstreth, W. T., Boerwinkle, E., Seshadri, S., Fornage, M. (2014) Associations of NINJ2 sequence variants with incident ischemic stroke in the Cohorts for Heart and Aging in Genomic Epidemiology (CHARGE) consortium PLoS ONE, 9, pp. e99798. (doi: 10.1371/journal.pone.0099798)

Lee, D., Rushworth, A., Sahu, S. K. (2014) A Bayesian localized conditional autoregressive model for estimating the health effects of air pollution Biometrics, 70, pp. 419-429. (doi: 10.1111/biom.12156)

Powell, H., Lee, D. (2014) Modelling spatial variability in concentrations of single pollutants and composite air quality indicators in health effects studies Journal of the Royal Statistical Society: Series A (Statistics in Society), 177, pp. 607-623. (doi: 10.1111/rssa.12034)

Aderhold, A., Husmeier, D., Grzegorczyk, M. (2014) Statistical inference of regulatory networks for circadian regulation Statistical Applications in Genetics and Molecular Biology, 13, pp. 227-273. (doi: 10.1515/sagmb-2013-0051)

Lin, H., Wang, M., Brody, J. A., Bis, J. C., Dupuis, J., Lumley, T., McKnight, B., Rice, K. M., Sitlani, C. M., Reid, J. G., Bressler, J., Liu, X., Davis, B. C., Johnson, A. D., O'Donnell, C. J., Kovar, C. L., Dinh, H., Wu, Y., Newsham, I., Chen, H., Broka, A., DeStefano, A. L., Gupta, M., Lunetta, K. L., Liu, C.-T., White, C. C., Xing, C., Zhou, Y., Benjamin, E. J., Schnabel, R. B., Heckbert, S. R., Psaty, B. M., Muzny, D. M., Cupples, L. A., Morrison, A. C., Boerwinkle, E. (2014) Strategies to design and analyze targeted sequencing data: cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium targeted sequencing study Circulation: Cardiovascular Genetics, 7, pp. 335-343. (doi: 10.1161/CIRCGENETICS.113.000350)

Eze, J.I., Scott, E.M., Pollock, K.G., Stidson, R., Miller, C.A., Lee, D. (2014) The association of weather and bathing water quality on the incidence of gastrointestinal illness in the west of Scotland Epidemiology and Infection, 142, pp. 1289-1299. (doi: 10.1017/S0950268813002148)

Prada Jiménez de Cisneros, J., Matthews, L., Mair, C., Stefan, T., Stear, M. J. (2014) The transfer of IgA from mucus to plasma and the implications for diagnosis and control of nematode infections Parasitology, 141, pp. 875-879. (doi: 10.1017/S0031182013002321)

Waldron, S., Scott, E. M., Vihermaa, L. E., Newton, J. (2014) Quantifying precision and accuracy of measurements of dissolved inorganic carbon stable isotopic composition using continuous-flow isotope-ratio mass spectrometry Rapid Communications in Mass Spectrometry, 28, pp. 1117-1126. (doi: 10.1002/rcm.6873)

Jones, W. R., Spence, M. J., Bowman, A. W., Evers, L., Molinari, D. A. (2014) A software tool for the spatiotemporal analysis and reporting of groundwater monitoring data Environmental Modelling and Software, 55, pp. 242-249. (doi: 10.1016/j.envsoft.2014.01.020)

Milotti, E., Vyshemirsky, V., Sega, M., Chignola, R. (2014) Corrigendum: Interplay between distribution of live cells and growth dynamics of solid tumours Scientific Reports, 4, (doi: 10.1038/srep03387)

Morrison, S., Fordyce, F.M., Scott, E.M. (2014) An initial assessment of spatial relationships between respiratory cases, soil metal content, air quality and deprivation indicators in Glasgow, Scotland, UK: relevance to the environmental justice agenda Environmental Geochemistry and Health, 36, pp. 319-332. (doi: 10.1007/s10653-013-9565-4)

Grzegorczyk, M., Aderhold, A., Smith, V. A., Husmeier, D. (2014) Inference of circadian regulatory networks Copicentro Granada S.L

Davies, V., Reeve, R., Harvey, W., Maree, F., Husmeier, D. (2014) Sparse Bayesian variable selection for the identification of antigenic variability in the Foot-and-Mouth disease virus Proceedings of Machine Learning Research, 33, pp. 149-158.

Lindsay, B. G., Markatou, M., Ray, S. (2014) Kernels, degrees of freedom and power properties of quadratic distance goodness of fit tests Journal of the American Statistical Association, 109, pp. 395-410. (doi: 10.1080/01621459.2013.836972)

Gupta, M. (2014) An evolutionary Monte Carlo algorithm for Bayesian block clustering of data matrices Computational Statistics and Data Analysis, 71, pp. 375- 391. (doi: 10.1016/j.csda.2013.07.006)

Lin, H., Sinner, M. F., Brody, J. A., Arking, D. E., Lunetta, K. L., Rienstra, M., Lubitz, S. A., Magnani, J. W., Sotoodehnia, N., McKnight, B., McManus, D. D., Boerwinkle, E., Psaty, B. M., Rotter, J. I., Bis, J. C., Gibbs, R. A., Muzny, D., Kovar, C. L., Morrison, A. C., Gupta, M., Folsom, A. R., Kääb, S., Heckbert, S. R., Alonso, A., Ellinor, P. T., Benjamin, E. J. (2014) Targeted sequencing in candidate genes for atrial fibrillation: the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) targeted sequencing study Heart Rhythm, 11, pp. 452-457. (doi: 10.1016/j.hrthm.2013.11.012)

Cobbold, C. A., Lutscher, F. (2014) Mean occupancy time: linking mechanistic movement models, population dynamics and landscape ecology to population persistence Journal of Mathematical Biology, 68, pp. 549-579. (doi: 10.1007/s00285-013-0642-1)

Gjini, E. A., Haydon, D. T., Barry, J. D., Cobbold, C. A. (2014) Revisiting the diffusion approximation to estimate evolutionary rates of gene family diversification Journal of Theoretical Biology, 341, pp. 111-122. (doi: 10.1016/j.jtbi.2013.10.001)

Miller, C., Magdalina, A.-M., Willows, R., Bowman, A., Scott, E., Lee, D., Burgess, C., Pope, L., Pannullo, F., Haggarty, R. (2014) Spatiotemporal statistical modelling of long-term change in river nutrient concentrations in England & Wales Science of the Total Environment, 466-7, pp. 914-923. (doi: 10.1016/j.scitotenv.2013.07.113)

O'Donnell, D., Rushworth, A., Bowman, A. W., Scott, E.M., Hallard, M. (2014) Flexible regression models over river networks Journal of the Royal Statistical Society: Series C (Applied Statistics), 63, pp. 47-63. (doi: 10.1111/rssc.12024)

Altieri, L., Cocchi, D., Pezzi, G., Scott, E. M., Ventrucci, M. (2014) Urban sprawl scatterplots for urban morphological zones data Ecological Indicators, 36, pp. 315-323. (doi: 10.1016/j.ecolind.2013.07.011)

Dowell, J., Weiss, S., Infield, D., Chandna, S. (2014) A Widely Linear Multichannel Wiener Filter for Wind Prediction (doi: 10.1109/SSP.2014.6884567)

Bollen, K. A., Harden, J. J., Ray, S., Zavisca, J. (2014) BIC and alternative Bayesian information criteria in the selection of structural equation models Structural Equation Modeling: A Multidisciplinary Journal, 21, pp. 1-19. (doi: 10.1080/10705511.2014.856691)

Millar, K., Bowman, A.W., Burns, D., McLaughlin, P., Moores, T., Morton, N.S., Musiello, T., Wallace, E., Wray, A., Welbury, R.R. (2014) Children's cognitive recovery after day-case general anesthesia: a randomized trial of propofol or isoflurane for dental procedures Pediatric Anesthesia, 24, pp. 201-207. (doi: 10.1111/pan.12316)

Lee, D., Mitchell, R. (2014) Controlling for localised spatio-temporal autocorrelation in long-term air pollution and health studies Statistical Methods in Medical Research, 23, pp. 488-506. (doi: 10.1177/0962280214527384)

Scott, E. M., Cocchi, D., Gemmell, J. C. (2014) Defining a fit for purpose statistically reliable sustainability indicator Sustainability Accounting, Management and Policy Journal, 5, pp. 262-267. (doi: 10.1108/SAMPJ-04-2014-0024)

Mitchell, R., Lee, D. (2014) Is there really a "wrong side of the tracks" in urban areas and does it matter for spatial analysis? Annals of the Association of American Geographers, 104, pp. 432-443. (doi: 10.1080/00045608.2014.892321)

Davies, V., Husmeier, D. (2014) Modelling transcriptional regulation with Gaussian processes Nova Science Publishers

Illian, J.B., Jones-Todd, C. (2014) Preventing Crime Through Spatial Modelling. (Scottish Institute of Policing Research) SIPR Annual report

Chanialidis, C., Evers, L., Neocleous, T., Nobile, A. (2014) Retrospective sampling in MCMC with an application to COM-Poisson regression Stat, 3, pp. 273-290. (doi: 10.1002/sta4.61)

Dowell, J., Weiss, S., Infield, D. (2014) Spatio-temporal Prediction of Wind Speed and Direction by Continuous Directional Regime (doi: 10.1109/PMAPS.2014.6960596)

Cheng, Y., Ray, S., Chang, M., Menon, S. (2014) Statistical monitoring of clinical trials with multiple co-primary endpoints using multivariate B-value Statistics in Biopharmaceutical Research, 6, pp. 241-250. (doi: 10.1080/19466315.2014.923324)

Bock, M., McColl, J. (2014) Using On-Line Quizzes to Help Students Learn Probability and Statistics