Dr Tereza Neocleous

  • Senior Lecturer (Statistics)

telephone: 01413306117
email: Tereza.Neocleous@glasgow.ac.uk

School Of Maths & Stats, Room 317 Maths & Stats Building, Phone: 330 6117, University Place, Glasgow, G12 8QQ

ORCID iDhttps://orcid.org/0000-0001-7792-4541

Research interests

I am an applied statistician interested in developing flexible models that enhance our understanding of data and facilitate inference. My research interests include quantile regression, survival data analysis, semiparametric models and multivariate data analysis. My main areas of application are biostatistics, epidemiology, forensic statistics, chemometrics and linguistics.

Research units

  • Statistics & Data Analytics
  • Nonparametric and semi-parametric statistics
  • Biostatistics, epidemiology, and health applications
  • Social and urban studies
  • Statistics in chemistry/physics

Publications

Selected publications

Lee, D. and Neocleous, T. (2010) Bayesian quantile regression for count data with application to environmental epidemiology. Journal of the Royal Statistical Society: Series C (Applied Statistics), 59(5), pp. 905-920. (doi: 10.1111/j.1467-9876.2010.00725.x)

Napier, G., Neocleous, T. and Nobile, A. (2015) A composite Bayesian hierarchical model of compositional data with zeros. Journal of Chemometrics, 9(2), pp. 96-108. (doi: 10.1002/cem.2681)

Chanialidis, C. , Evers, L. , Neocleous, T. and Nobile, A. (2018) Efficient Bayesian inference for COM-Poisson regression models. Statistics and Computing, 28(3), pp. 595-608. (doi: 10.1007/s11222-017-9750-x)

Biosa, G., Giurghita, D., Alladio, E., Vincenti, M. and Neocleous, T. (2020) Evaluation of forensic data using logistic regression-based classification methods and an R Shiny implementation. Frontiers in Chemistry, 8, 738. (doi: 10.3389/fchem.2020.00738) (PMID:33195014) (PMCID:PMC7609892)

All publications

List by: Type | Date

Jump to: 2022 | 2020 | 2018 | 2017 | 2016 | 2015 | 2014 | 2011 | 2010 | 2009 | 2008
Number of items: 16.

2022

Szili, B., Niu, M. and Neocleous, T. (2022) A Structural Learning Method for Graphical Models. In: 4th International Conference on Statistics: Theory and Applications (ICSTA'22), Prague, Czech Republic, 28-30 Jul 2022, p. 113. ISBN 9781990800085 (doi: 10.11159/icsta22.113)

2020

Biosa, G., Giurghita, D., Alladio, E., Vincenti, M. and Neocleous, T. (2020) Evaluation of forensic data using logistic regression-based classification methods and an R Shiny implementation. Frontiers in Chemistry, 8, 738. (doi: 10.3389/fchem.2020.00738) (PMID:33195014) (PMCID:PMC7609892)

2018

Chanialidis, C. , Evers, L. , Neocleous, T. and Nobile, A. (2018) Efficient Bayesian inference for COM-Poisson regression models. Statistics and Computing, 28(3), pp. 595-608. (doi: 10.1007/s11222-017-9750-x)

2017

Alexander, C. , Stuart-Smith, J. , Neocleous, T. and Evers, L. (2017) Using Chain Graph Models for Structural Inference With an Application to Linguistic Data. In: 32nd International Workshop on Statistical Modelling, Groningen, Netherlands, 03-07 Jul 2017, pp. 270-274.

2016

Martyna, A., Zadora, G., Neocleous, T. , Michalska, A. and 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) (PMID:27282749)

2015

Napier, G. , Nobile, A. and 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)

Napier, G., Neocleous, T. and Nobile, A. (2015) A composite Bayesian hierarchical model of compositional data with zeros. Journal of Chemometrics, 9(2), pp. 96-108. (doi: 10.1002/cem.2681)

2014

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)

2011

Neocleous, T. , Aitken, C. and Zadora, G. (2011) Transformations for compositional data with zeros with an application to forensic evidence evaluation. Chemometrics and Intelligent Laboratory Systems, 109(1), pp. 77-85. (doi: 10.1016/j.chemolab.2011.08.003)

2010

Lee, D. and Neocleous, T. (2010) Bayesian quantile regression for count data with application to environmental epidemiology. Journal of the Royal Statistical Society: Series C (Applied Statistics), 59(5), pp. 905-920. (doi: 10.1111/j.1467-9876.2010.00725.x)

Zadora, G. and Neocleous, T. (2010) Evidential value of physicochemical data-comparison of methods of glass database creation. Journal of Chemometrics, 24(7-8), pp. 367-378. (doi: 10.1002/cem.1276)

Dowlman, E. A., Martin, N. C., Foy, M. J., Lochner, T. and Neocleous, T. (2010) The prevalence of mixed DNA profiles on fingernail swabs. Science and Justice, 50(2), pp. 64-71. (doi: 10.1016/j.scijus.2009.03.005)

Zadora, G., Neocleous, T. and Aitken, C. (2010) A Two-Level Model for Evidence Evaluation in the Presence of Zeros. Journal of Forensic Sciences, 55(2), pp. 371-384. (doi: 10.1111/j.1556-4029.2009.01316.x)

2009

Neocleous, T. and Portnoy, S. (2009) Partially linear censored quantile regression. Lifetime Data Analysis, 15(3), pp. 357-378. (doi: 10.1007/s10985-009-9117-5)

Zadora, G. and Neocleous, T. (2009) Likelihood ratio model for classification of forensic evidence. Analytica Chimica Acta, 642(1-2), pp. 266-278. (doi: 10.1016/j.aca.2008.12.013)

2008

Neocleous, T. and Portnoy, S. (2008) On monotonicity of regression quantile functions. Statistics and Probability Letters, 78(10), pp. 1226-1229. (doi: 10.1016/j.spl.2007.11.024)

This list was generated on Tue Mar 28 03:39:42 2023 BST.
Jump to: Articles | Conference Proceedings
Number of items: 16.

Articles

Biosa, G., Giurghita, D., Alladio, E., Vincenti, M. and Neocleous, T. (2020) Evaluation of forensic data using logistic regression-based classification methods and an R Shiny implementation. Frontiers in Chemistry, 8, 738. (doi: 10.3389/fchem.2020.00738) (PMID:33195014) (PMCID:PMC7609892)

Chanialidis, C. , Evers, L. , Neocleous, T. and Nobile, A. (2018) Efficient Bayesian inference for COM-Poisson regression models. Statistics and Computing, 28(3), pp. 595-608. (doi: 10.1007/s11222-017-9750-x)

Martyna, A., Zadora, G., Neocleous, T. , Michalska, A. and 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) (PMID:27282749)

Napier, G. , Nobile, A. and 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)

Napier, G., Neocleous, T. and Nobile, A. (2015) A composite Bayesian hierarchical model of compositional data with zeros. Journal of Chemometrics, 9(2), pp. 96-108. (doi: 10.1002/cem.2681)

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)

Neocleous, T. , Aitken, C. and Zadora, G. (2011) Transformations for compositional data with zeros with an application to forensic evidence evaluation. Chemometrics and Intelligent Laboratory Systems, 109(1), pp. 77-85. (doi: 10.1016/j.chemolab.2011.08.003)

Lee, D. and Neocleous, T. (2010) Bayesian quantile regression for count data with application to environmental epidemiology. Journal of the Royal Statistical Society: Series C (Applied Statistics), 59(5), pp. 905-920. (doi: 10.1111/j.1467-9876.2010.00725.x)

Zadora, G. and Neocleous, T. (2010) Evidential value of physicochemical data-comparison of methods of glass database creation. Journal of Chemometrics, 24(7-8), pp. 367-378. (doi: 10.1002/cem.1276)

Dowlman, E. A., Martin, N. C., Foy, M. J., Lochner, T. and Neocleous, T. (2010) The prevalence of mixed DNA profiles on fingernail swabs. Science and Justice, 50(2), pp. 64-71. (doi: 10.1016/j.scijus.2009.03.005)

Zadora, G., Neocleous, T. and Aitken, C. (2010) A Two-Level Model for Evidence Evaluation in the Presence of Zeros. Journal of Forensic Sciences, 55(2), pp. 371-384. (doi: 10.1111/j.1556-4029.2009.01316.x)

Neocleous, T. and Portnoy, S. (2009) Partially linear censored quantile regression. Lifetime Data Analysis, 15(3), pp. 357-378. (doi: 10.1007/s10985-009-9117-5)

Zadora, G. and Neocleous, T. (2009) Likelihood ratio model for classification of forensic evidence. Analytica Chimica Acta, 642(1-2), pp. 266-278. (doi: 10.1016/j.aca.2008.12.013)

Neocleous, T. and Portnoy, S. (2008) On monotonicity of regression quantile functions. Statistics and Probability Letters, 78(10), pp. 1226-1229. (doi: 10.1016/j.spl.2007.11.024)

Conference Proceedings

Szili, B., Niu, M. and Neocleous, T. (2022) A Structural Learning Method for Graphical Models. In: 4th International Conference on Statistics: Theory and Applications (ICSTA'22), Prague, Czech Republic, 28-30 Jul 2022, p. 113. ISBN 9781990800085 (doi: 10.11159/icsta22.113)

Alexander, C. , Stuart-Smith, J. , Neocleous, T. and Evers, L. (2017) Using Chain Graph Models for Structural Inference With an Application to Linguistic Data. In: 32nd International Workshop on Statistical Modelling, Groningen, Netherlands, 03-07 Jul 2017, pp. 270-274.

This list was generated on Tue Mar 28 03:39:42 2023 BST.

Supervision

I welcome enquiries from students interested in PhD or MSc by Research projects in the following areas:

Forensic statistics

Multivariate data analysis for hierarchical/longitudinal data

Quantile regression applications in health and social science

Current PhD supervision:

Taweesak Changgam (Ph.D 2020-), jointly supervised with C. Anderson. Models for child growth.

Jorge Sanchez (Ph.D. 2020-), jointly supervised with N. Dean. Classification using finite mixtures of contaminated normal distributions.

Catherine Holland (Ph.D. 2020-), jointly supervised with G. Napier and O. Stoner. Bayesian models for compositional data.

 

Completed student research projects:

Dimitra Eleftheriou (Ph.D. 2017-2022). Bayesian hierarchical modelling for biomarkers with applications to doping detection and prostate cancer prediction.

Craig Alexander (Ph.D. 2014-18, jointly supervised with L. Evers and J. Stuart-Smith). Multilevel models for the analysis of linguistic data.

Charalampos Chanialidis (Ph.D., 2011-15, jointly supervised with L. Evers). Bayesian mixture models for count data.

Gary Napier (Ph.D., 2010-14, jointly supervised with A. Nobile). A Bayesian hierarchical model of compositional data with zeros: classification and evidence evaluation of forensic glass.

Elizabeth Irwin (M.Sc. by research, 2012-13). Statistical methods of constructing growth charts.

Laura Allison (M.Sc. by research, 2010-11). Evaluation of transfer evidence.

Gary Napier (M.Sc. by research, 2009-10, jointly supervised with S. Senn). Modelling obesity in Scotland.

Teaching

I teach a variety of statistics courses and supervise student projects at the undergraduate and postgraduate level. I am interested in ways of teaching that encourage student engagement and interaction, and in designing assignments that enable students to learn by doing. In addition to in-person teaching, in recent years I have worked on designing and delivering online courses and assessments for the Online MSc in Data Analytics. 


A portrait of Tereza Neocleous