Dr Ludger Evers

  • Lecturer (Statistics)

telephone: 5174
email: Ludger.Evers@glasgow.ac.uk

R322
Mathematics & Statistics Building
University Place
Glasgow

Research interests

Research Interests

My research focuses on methodological aspects of statistical methods in machine learning, partition and mixture-based models, and non-linear dimension reduction. Application areas of my research include astronomy, engineering, environmental modelling and microarray data analysis.

Research Groups


Publications

List all by: Type | Date

Jump to: 2017 | 2016 | 2015 | 2014 | 2013 | 2012 | 2010 | 2009 | 2008 | 2005
Number of items: 19.

2017

Venkatasubramaniam, A., Evers, L. and Ampountolas, K. (2017) Spatio-Temporal Clustering of Urban Traffic Networks. 2017 Joint Statistical Meetings (JSM), Maryland, MD, 29 Jul-3 Aug 2017. (Submitted)

Venkatasubramaniam, A., Evers, L. and Ampountolas, K. (2017) Spatio-Temporal Clustering of Traffic Networks. 32nd International Workshop on Statistical Modelling (IWSM), Groningen, The Netherlands, 3-7 Jul 2017. (Submitted)

Evers, L. and Heaton, T. (2017) Locally adaptive tree-based thresholding using the treethresh package in R. Journal of Statistical Software, 78, Code S 2. (doi:10.18637/jss.v078.c02)

Chanialidis, C., Evers, L., Neocleous, T. and Nobile, A. (2017) Efficient Bayesian inference for COM-Poisson regression models. Statistics and Computing, 28(3), pp. 595-608. (doi:0.1007/s11222-017-9750-x)

2016

Venkatasubramaniam, A., Evers, L. and Ampountolas, K. (2016) Distance Dependent Chinese restaurant process for Spatio-Temporal Clustering of Urban Traffic Networks. 22nd International Conference on Computational Statistics (COMPSTAT 2016), Oviedo, Spain, 23-26 Aug 2016. (Submitted)

2015

Evers, L., Molinari, D.A., Bowman, A.W. , Jones, W.R. and Spence, M.J. (2015) Efficient and automatic methods for flexible regression on spatiotemporal data, with applications to groundwater monitoring. Environmetrics, 26(6), pp. 431-441. (doi:10.1002/env.2347)

Stuart-Smith, J., Lennon, R., Macdonald, R., Robertson, D., Soskuthy, M., Jose, B. and Evers, L. (2015) A Dynamic Acoustic View of Real-Time Change in Word-Final Liquids in Spontaneous Glaswegian. In: 18th International Congress of Phonetic Sciences, Glasgow,, Glasgow, UK, 10-14 Aug 2015, ISBN 9780852619414

2014

Jones, W. R., Spence, M. J., Bowman, A. W. , Evers, L. and 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)

Chanialidis, C., Evers, L., Neocleous, T. and Nobile, A. (2014) Retrospective sampling in MCMC with an application to COM-Poisson regression. Stat, 3(1), pp. 273-290. (doi:10.1002/sta4.61)

2013

Chanialidis, C., Craigmile, P., Davies, V. , Dean, N. , Evers, L., Filiippone, M., Gupta, M., Ray, S. and Rogers, S. (2013) Discussion of Henning and Liao: How to find an appropriate clustering for mixed type variables with application to socio-economic stratification. Journal of the Royal Statistical Society: Series C. 62, 309-369. Discussion Paper. Springer.

2012

Einbeck, J., Isaac, B., Evers, L. and Parente, A. (2012) Penalized Regression on Principal Manifolds with Application to Combustion Modelling. In: Proceedings of the 27th International Workshop on Statistical Modelling, pp. 117-122.

Molinari, D., Evers, L. and Bowman, A. (2012) Smoothing Parameter Selection for Spatiotemporal Models with Application to the Analysis of Contaminants in Groundwater. In: Proceedings of the 27th International Workshop on Statistical Modelling, Prague, Czech Republic, 16-20 July 2012,

2010

Einbeck, J., Evers, L. and Powell, B. (2010) Data Compression and Regression Through Local Principal Curves and Surfaces. International Journal of Neural Systems, 20(3), pp. 177-192. (doi:10.1142/S0129065710002346)

Einbeck, J., Evers, L. and Hinchliff, K. (2010) Data compression and regression based on local principal curves. In: Fink, A., Lausen, B., Seidel, W. and Ultsch, A. (eds.) Advances in Data Analysis, Data Handling and Business Intelligence. Springer, pp. 701-712. (doi:10.1007/978-3-642-01044-6_64)

Einbeck, J. and Evers, L. (2010) Localized Regression on Principal Manifolds. In: 25th International Workshop on Statistical Modelling (IWSM 2010), Glasgow, UK, 5-9 Jul 2010,

2009

Evers, L. and Heaton, T. J. (2009) Locally Adaptive Tree-Based Thresholding. Journal of Computational and Graphical Statistics, 18(4), pp. 961-977. (doi:10.1198/jcgs.2009.07109)

2008

Evers, L. and Messow, C.-M. (2008) Sparse kernel methods for high-dimensional survival data. Bioinformatics, 24(14), pp. 1632-1638. (doi:10.1093/bioinformatics/btn253)

Einbeck, J., Evers, L. and Bailer-Jones, C. (2008) Representing complex data using localized principal components with application to astronomical data. Lecture Notes in Computational Science and Engineering, 58, pp. 178-201. (doi:10.1007/978-3-540-73750-6_7)

2005

Einbeck, J., Tutz, G. and Evers, L. (2005) Local principal curves. Statistics and Computing, 15(4), pp. 301-313. (doi:10.1007/s11222-005-4073-8)

This list was generated on Sat Sep 22 14:03:40 2018 BST.
Number of items: 19.

Articles

Evers, L. and Heaton, T. (2017) Locally adaptive tree-based thresholding using the treethresh package in R. Journal of Statistical Software, 78, Code S 2. (doi:10.18637/jss.v078.c02)

Chanialidis, C., Evers, L., Neocleous, T. and Nobile, A. (2017) Efficient Bayesian inference for COM-Poisson regression models. Statistics and Computing, 28(3), pp. 595-608. (doi:0.1007/s11222-017-9750-x)

Evers, L., Molinari, D.A., Bowman, A.W. , Jones, W.R. and Spence, M.J. (2015) Efficient and automatic methods for flexible regression on spatiotemporal data, with applications to groundwater monitoring. Environmetrics, 26(6), pp. 431-441. (doi:10.1002/env.2347)

Jones, W. R., Spence, M. J., Bowman, A. W. , Evers, L. and 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)

Chanialidis, C., Evers, L., Neocleous, T. and Nobile, A. (2014) Retrospective sampling in MCMC with an application to COM-Poisson regression. Stat, 3(1), pp. 273-290. (doi:10.1002/sta4.61)

Einbeck, J., Evers, L. and Powell, B. (2010) Data Compression and Regression Through Local Principal Curves and Surfaces. International Journal of Neural Systems, 20(3), pp. 177-192. (doi:10.1142/S0129065710002346)

Evers, L. and Heaton, T. J. (2009) Locally Adaptive Tree-Based Thresholding. Journal of Computational and Graphical Statistics, 18(4), pp. 961-977. (doi:10.1198/jcgs.2009.07109)

Evers, L. and Messow, C.-M. (2008) Sparse kernel methods for high-dimensional survival data. Bioinformatics, 24(14), pp. 1632-1638. (doi:10.1093/bioinformatics/btn253)

Einbeck, J., Evers, L. and Bailer-Jones, C. (2008) Representing complex data using localized principal components with application to astronomical data. Lecture Notes in Computational Science and Engineering, 58, pp. 178-201. (doi:10.1007/978-3-540-73750-6_7)

Einbeck, J., Tutz, G. and Evers, L. (2005) Local principal curves. Statistics and Computing, 15(4), pp. 301-313. (doi:10.1007/s11222-005-4073-8)

Book Sections

Einbeck, J., Evers, L. and Hinchliff, K. (2010) Data compression and regression based on local principal curves. In: Fink, A., Lausen, B., Seidel, W. and Ultsch, A. (eds.) Advances in Data Analysis, Data Handling and Business Intelligence. Springer, pp. 701-712. (doi:10.1007/978-3-642-01044-6_64)

Research Reports or Papers

Chanialidis, C., Craigmile, P., Davies, V. , Dean, N. , Evers, L., Filiippone, M., Gupta, M., Ray, S. and Rogers, S. (2013) Discussion of Henning and Liao: How to find an appropriate clustering for mixed type variables with application to socio-economic stratification. Journal of the Royal Statistical Society: Series C. 62, 309-369. Discussion Paper. Springer.

Conference or Workshop Item

Venkatasubramaniam, A., Evers, L. and Ampountolas, K. (2017) Spatio-Temporal Clustering of Urban Traffic Networks. 2017 Joint Statistical Meetings (JSM), Maryland, MD, 29 Jul-3 Aug 2017. (Submitted)

Venkatasubramaniam, A., Evers, L. and Ampountolas, K. (2017) Spatio-Temporal Clustering of Traffic Networks. 32nd International Workshop on Statistical Modelling (IWSM), Groningen, The Netherlands, 3-7 Jul 2017. (Submitted)

Venkatasubramaniam, A., Evers, L. and Ampountolas, K. (2016) Distance Dependent Chinese restaurant process for Spatio-Temporal Clustering of Urban Traffic Networks. 22nd International Conference on Computational Statistics (COMPSTAT 2016), Oviedo, Spain, 23-26 Aug 2016. (Submitted)

Conference Proceedings

Stuart-Smith, J., Lennon, R., Macdonald, R., Robertson, D., Soskuthy, M., Jose, B. and Evers, L. (2015) A Dynamic Acoustic View of Real-Time Change in Word-Final Liquids in Spontaneous Glaswegian. In: 18th International Congress of Phonetic Sciences, Glasgow,, Glasgow, UK, 10-14 Aug 2015, ISBN 9780852619414

Einbeck, J., Isaac, B., Evers, L. and Parente, A. (2012) Penalized Regression on Principal Manifolds with Application to Combustion Modelling. In: Proceedings of the 27th International Workshop on Statistical Modelling, pp. 117-122.

Molinari, D., Evers, L. and Bowman, A. (2012) Smoothing Parameter Selection for Spatiotemporal Models with Application to the Analysis of Contaminants in Groundwater. In: Proceedings of the 27th International Workshop on Statistical Modelling, Prague, Czech Republic, 16-20 July 2012,

Einbeck, J. and Evers, L. (2010) Localized Regression on Principal Manifolds. In: 25th International Workshop on Statistical Modelling (IWSM 2010), Glasgow, UK, 5-9 Jul 2010,

This list was generated on Sat Sep 22 14:03:40 2018 BST.

Supervision

Current PhD students

Craig Alexander (Recovering the dynamics of talk: tracking temporal dependence in multilevel models for speech )
Marnie McLean (Optimal spatio-temporal modelling and monitoring of groundwater )
Ivona Voroneckaja
Dimitra Eleftheriou
Ashwini Venkatasubramaniam

Former PhD students

  • Rob Donald (Predicting Hypotensive Episodes in the Traumatic Brain Injury Domain, 2014)
  • Daniel Molinari (Spatiotemporal Modelling of Groundwater Contaminants, 2014)

Teaching

This year I am teaching the following courses:

  • Statistics 2X
  • Introduction to R