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

All publications | View selected publications

List all by: Type | Date

Jump to: 2017 | 2015 | 2014 | 2013 | 2012 | 2010 | 2009 | 2008 | 2005
Number of items: 16.

2017

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, (doi:0.1007/s11222-017-9750-x) (Early Online Publication)

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., Daies, 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. UNSPECIFIED.

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 Sun Sep 24 19:25:45 2017 BST.
Number of items: 16.

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, (doi:0.1007/s11222-017-9750-x) (Early Online Publication)

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., Daies, 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. UNSPECIFIED.

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 Sun Sep 24 19:25:45 2017 BST.

Grants


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 )
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

Additional information