Dr Julian Stander
Associate Professor in Mathematics and Statistics
School of Computing, Electronics and Mathematics (Faculty of Science and Engineering)
an MA degree in Mathematics from the University of Oxford (First Class Honours Moderations, First Class Honours Finals, Scholar of Hertford College)
a Diploma in Mathematical Statistics (with distinction and University prize) from the University of Cambridge (Darwin College)
a PhD from the University of Bath for a thesis entitled Some Topics in Statistical Image Analysis.
I am a Senior Fellow of the Higher Education Academy.
I have been at the University of Plymouth since October 1993. Before coming to Plymouth, I held a Royal Society European Science Exchange Programme Fellowship at the Istituto per le Applicazioni del Calcolo,CNR, Rome. I worked again at this institute for six months during 2000 supported by the European Union's research network on Statistical and Computational Methods for the Analysis of Spatial Data.
I am a Senior Fellow of the Higher Education Academy.
I was a Council member of the Royal Statistical Society for four years.
I am also the treasurer for COPS, the UK and Ireland Committee of Professors of Statistics.
I am Chair and Treasurer of the Royal Statistical Society South West Group.
I served for many years on the committees of the General Applications Section (Secretary and Chair).
I was Associate Editor for the Journal of the Royal Statistical Society D "The Statistician".
I was chairman of the Organising Committee for RSS 2002, which was held in Plymouth.
I have also organized other meetings.
In addition am a member of the Bernoulli Society, the British-Italian Society, the Venice in Peril and the British Flute Society.
Roles on external bodies
Chairman and Treasurer of the South West Local Group of the Royal Statistical Society.
Treasurer of the UK and Ireland Committee of Professors of Statistics.
I was a Council Member of the Royal Statistical Society for four years.
I was Secretary and Chair of the General Applications Section, Royal Statistical Society for many years.
Committee Member of the Statistical Image Analysis and Processing Study Group.
Member of the President Nominating Committee, Royal Statistical Society.
Chairman of the Local Organising Committee for RSS 2002, the international conference of the Royal Statistical Society
I was invited to be a member of the three person International Review of Research of the Department of Statistical Science, University of Bologna, Italy, 2003.
I have served as an External Examiner at a number of universities (Reading, Oxford, Bath, etc).
I am delighted to be Runner Up for the SSTAR Postgraduate Teacher/Supervisor of the Year Award 2017/18. I am touched, honoured and grateful that our students kindly nominated me.
I am a Senior Fellow of the Higher Education Academy.
I teach with colleagues on the following modules and Doctoral College short courses:
MATH1608PP Understanding Big Data from Social Networks
MATH501 Modelling and Analytics for Data Science [Module Leader]
MATH3613 Data Modelling [Module Leader]
MATH500 Big Data and Social Network Visualisation
Introduction to R
Advanced to R
I help to look after the BSc (Hons) Exchange: Maths/Stats.
I am interested in teaching Data Science, using R to improve teaching and learning, visualizing student assessment and feedback data, and communicating statistical and scientific ideas to a variety of audience.
Further details are available upon request. Thank you.
Staff serving as external examiners
I have served as External Examiner for:
the MSc in Applied Statistics, University of Oxford;
the Statistics Programmes, University of Reading;
the Statistics Programmes, University of Bath;
For many years I analysed the annual Plymouth and South West Co-operative Society Staff Questionnaire. I provide help with data analysis across the University.
Research degrees awarded to supervised students
I have supervised six successful PhD students.
I have supervised many Italian project students.
Grants & contracts
- Centre for Mathematical Sciences (CMS)
Papers Submitted or Under Review
Stander, M. and Stander, J. (2018) A simple method for correcting for the Will Rogers phenomenon.
Eichenseer, K., Balthasar, U., Smart, C. W, Stander, J. and Kiessling, W. (2018) Amid-Phanerozoic revolution in the controlling factors of ecological success.
Stander, J.,Dalla Valle, L., Taglioni, C., Liseo, B., Wade, A. and Cortina-Borja, M. (2018) Bayesian inference for bivariate copulas with additive models for dependence, marginal location, scale and shape: an application in paediatric ophthalmology.
Cai, Y. and Stander,J. (2018) The threshold GARCH model: estimation and density forecasting for financial returns.
Academic Journal Publications
33. Dalla Valle, L., Stander, J., Gresty, K.,Eales, J. and Wei, Y. (2018) Stakeholder perspectives on graphical tools for visualising student assessment and feedback data. Research in Learning Technology. Volume 26, No. 1997.
32. Stander, J., Dalla Valle, L. and Cortina Borja, M. (2017) A Bayesian survival analysis of a historical dataset: how long do popes live? The American Statistician, Teachers Corner, in press. http://amstat.tandfonline.com/doi/abs/10.1080/00031305.2017.1328374#.WkvIEFSFjUI
31. Stander, J. and Dalla Valle, L. (2017) On enthusing students about Big Data and social media visualization and analysis using R, RStudio and RMarkdown. Journal of Statistics Education, 25, 2, 60–67. Lesson outlines presented as Supplementary Material. http://tandfonline.com/doi/full/10.1080/10691898.2017.1322474
30. Al-Saadony, M., Hewson, P. and Stander, J. (2013) Cholesky decomposition for the Vasicek interest rate model. International Journal of Statistics and Probability, 2, 22–28.
29, Cai, Y., Stander, J. and Davies, N. (2012) A new Bayesian approach to quantile autoregressive time series model estimation and forecasting. Journal of Time Series Analysis, 33, 683–698.
28. Stander, J. and Eales, J. (2011) Using R for teaching financial mathematics and statistics. MSOR Connections, 11, 1,7–11.
27. Thompson, P., Cai, Y., Moyeed, R.,Reeve, D. and Stander, J. (2010) Bayesian nonparametric quantile regression using splines. ComputationalStatistics & Data Analysis, 54,1138–1150.
26. Eales, J. and Stander, J. (2009) Using Minitab for teaching statistics in higher education. MSOR Connections, 9, 3,39–41.
25. Thompson, P., Cai, Y., Reeve, D. and Stander, J. (2009) Automated threshold selection methods for extreme wave analysis. Coastal Engineering, 56, 1013–1021.
24. De Pasquale, F. and Stander, J. (2009) A multi-scale method based on non-parametric deformable templates for medical image analysis. Pattern Analysis and Applications, 12, 179–192.
23. Cai, Y. and Stander, J. (2008) Quantile self-exciting threshold autoregressive time series models. Journal of Time Series Analysis, 29, 186–202.
22. Yu, K. and Stander, J. (2007) Bayesian analysis of a Tobit quantile regression model. Journal of Econometrics, 137, 260–276.
21. Brooker,S., Alexander. N., Geiger, S., Moyeed, R. A., Stander, J., Fleming, F., Hotez, P., Correa-Oliveira, R. and Bethony, J. (2006) Contrasting patterns in the small-scale heterogeneity ofhuman helminth infections in urban and rural environments in Brazil. InternationalJournal for Parasitology, 36,1143–1151.
20. Polettini S. and Stander,J. (2005) Bayesian models for risk estimation in statistical disclosure limitation. Quaderni di Statistica, 7, 69–90.
19. De Pasquale, F., Barone, P., Sebastiani, G. and Stander, J. (2004) Bayesian analysis of dynamic Magnetic Resonance breast images. Applied Statistics, 53, 475–493.
18. Alexander, N. D., Moyeed, R. A., Hyun, P. J., Dimber, Z. B., Bockarie, M. J., Stander, J., Grenfell, B. T., Kazura,J. W. and Alpers, M. P. (2003) Spatial variation of Anopheles-transmitted Wuchereria bancrofti and Plasmodium falciparum infection densities in Papua NewGuinea. Filaria Journal, 2003, 2:14.
17. Franconi, L. and Stander, J. (2003) Spatial and non-spatial model-based protection for the release of business microdata. Statistics and Computing, 13,295–305.
16. Polettini, S. and Stander, . (2003) A Comment on ‘A Theoretical Basis for Perturbation Methods’ by Krishnamurty Muralidhar and Rathindra Sarathy. Statistics and Computing, 13,337–338.
15. Barone, P., Sebastiani, G. and Stander, J. (2002) Over-relaxation methods and coupled Markov chains for Monte Carlo simulation. Statistics and Computing, 12, 17–26.
14. Franconi, L. and Stander, J. (2002) Model based disclosure limitation for business microdata. Journal of the Royal Statistical Society D, 51, 51–61.
13. Ambroze, A., Wade, G., Serdean, C., Tomlinson M., Stander, J. and Borda, M. (2001) Turbocode protection of a video watermark channel. IEEProc.-Vis. Image Signal Process., 148,54–58.
12. Barone, P., Sebastiani, G. and Stander, J. (2001) General over-relaxation Markov chain Monte Carlo algorithms for Gaussian densities. Statistics and Probability Letters, 52, 115–124.
11. Alexander, N., Moyeed, R. and Stander, J. (2000) Spatial modelling of individual-level parasite counts using the negative binomial distribution. Biostatistics,1, 453–463.
10. Luan, J., Stander,J. and Wright, D. (2000) A filter function algorithm for the detection of solid objects in noisy images. Statistica Applicata, 12, 407–423.
9. Luan, J., Stander, J. and Wright, D. (1998) On shape detection in noisy images with particular reference to ultrasonography. Statistics and Computing, 8, 377–389.
8. Frigessi, A., Martinelli, F. and Stander. J. (1997) Computational complexity of Markov chain Monte Carlo methods for finite Markov random fields. Biometrika, 84, 1–18.
7. Wright, D., Stander, J. and Nicolaides, K. (1997) Non-parametric density estimation and discrimination from images of shape. Applied Statistics, 46, 365–380.
6. Wright, D. and Stander, J. (1996) S-PLUS version 3.1, Release 1 for Windows. British Journal of Mathematical and Statistical Psychology, 49, 206–208.
5. Stander, J.and Silverman, B. W. (1995) Minimax estimation of linear functionals, particularly in nonparametric regression and positron emission tomography. Computational Statistics, 10, 259–283.
4. Frigessi, A. and Stander, J. (1994) Informative priors for the Bayesian classification of satellite images. Journal of the American Statistical Association, 89, 703–709.
3. Stander, J. and Silverman, B. W. (1994) Temperature schedules for simulated annealing. Statistics and Computing, 4, 21–32.
2. Silverman, B. W., Jennison, C., Stander, J. and Brown, T. C. (1990) The specification of edge penalties for regular and irregular pixel images. IEEE Transactions on Pattern Analysis and Machine Intelligence, PAMI–12, 1017–1024.
1. Stander,J., Farrington, D. P., Hill, G. and Altham, P. M. E. (1989) Markov chain analysis and specialization in criminal careers. BritishJournal of Criminology, 29,317–335.
Yu,K., Lu, Z. and Stander, J. (2003) Quantile regression: applications and current research areas. Journal of the Royal Statistical Society D, 52, 331–350.
Contribution to Discussions
2. Stander, J. and Dalla Valle, L. (2017) Contribution to the Discussion on the paper by Cannings,T. I. and Samworth, R. J. (2017) Random-projection ensemble classification. Journal of the Royal Statistical Society B, 79, 959–1035.
1. Stander, J. and Moyeed, R. (2011) Contribution to the Discussion on the paper by Wild, C.J., Pfannkuch, M., Regan, M. and Horton, N. J. (2011) Towards more accessible conceptions of statistical inference. Journal of the Royal Statistical Society A, 174, 247–295.
Contributions to Edited Works
2. Polettini, S. and Stander, J. (2004) A Bayesian hierarchical model approach to risk estimation in statistical disclosure limitation. In Domingo-Ferrer, J. and Torra, V. (Eds.) Privacy in Statistical Databases. Berlin: Springer-Verlag, pp. 247–261.
1. Polettini, S., Franconi, L. and Stander, J. (2002) Model based disclosure protection. In Domingo-Ferrer, J. (Ed.) Inference Control in Statistical Databases: from Theory to Practice. Berlin: Springer-Verlag, pp. 83–96.
2. James, G., Burley, D. M., Steele, N., Clements, R., Searl, J. W., Dyke, P.,Wright, J., Craven, M., Reis, T. and Stander,J. (2018) Advanced Modern Engineering Mathematics, Fifth Edition. Prentice Hall. To appear.
1. Franconi, L., Stander, J. and Pezzulli, S. (1996) Statistica: Esercizi per le Scienze Applicate. Tutor Series. Etas Libri. Milano Italy. 352 pages.
Burridge,J. Franconi, L., Polettini, S. and Stander, J. (2002) A methodological framework for statistical disclosure limitation of business microdata. Technical Report1.1-D4, CASC Project.
3. Stander, J. (1997) Markov chain Monte Carlo in practice (review). Journal of the Royal Statistical Society A, 160,158–159.
2. Stander, J. (1990) Statistical applications in criminal justice (review). Journal of the Royal Statistical Society D, 39,469.
1. Stander, J. (1990) Statistics for GCSE (review). Journal of the Royal Statistical Society D, 39, 92–93.
10.Cortina Borja, M. and Stander, J.(2018) Visualising ages and life trajectories of Prime Ministers of the United Kingdom. Significance. https://www.significancemagazine.com/politics/581-visualising-ages-and-life-trajectories-of-prime-ministers-of-the-united-kingdom.
9. Cangelosi, S., DallaValle, L. and Stander, J. (2017) Visualising regional data using the geofacet R package. Significance. https://www.significancemagazine.com/politics/561-visualising-regional-data-using-the-geofacet-r-package.
8. Cortina Borja, M., Stander, J. and Dalla Valle, L. (2016) Brexit: surname diversity and voting patterns. Significance, 13, 4, pages 8–9. Available online (expanded version) at https://www.statslife.org.uk/politics/2943-the-eu-referendum-surname-diversity-and-voting-patterns.
7. Stander, J., Dalla Valle, L. and Cortina Borja, M. (2016) How long can Pope Francis expect to live? Significance, 13, 1, pages 12–13. Available online (expanded version) at https://www.statslife.org.uk/culture/2686-statistically-speaking-how-long-can-pope-francis-expect-to-live.
6. Stander, J., Dalla Valle, L. and Contina Borja, M. (2016) Sentiments, surnames and so long EU. Communicator, Autumn 2016 – Special Supplement Science Communication. Pages 19–23.
5. Stander, J., Dalla Valle, L., Eales, J., Baldino, A. and Cortina Borja, M. (2016) The EU referendum: extracting insights from Facebook using R. Significance. https://www.statslife.org.uk/politics/2889-what-information-can-we-extract-from-social-media-about-the-uk-s-eu-referendum. Published19/5/2016, updated 20/6/2016.
4. Cortina Borja, M. and Stander, J. (2015) How Frank Wilcoxon helped statisticians walk thenon-parametric path. Significance. https://www.statslife.org.uk/history-of-stats-science/2590-how-frank-wilcoxon-helped-statisticians-walk-the-non-parametric-path.
3. Hewson, P., Kalinauskaite, A., Stander, J. and Cai, Y. (2010) Barefoot statisticians. Significance, 7, 4, 182–184.
2. Stander,J. (1998) Image analysis – a modern application of mathematics. Public Awareness and Schools Support for Mathematics, 4. https://plus.maths.org/content/os/issue4/stander/index.
1. Stander,J. (1998) Solution to the taxi problem revisited. Public Awareness and Schools Support for Mathematics, 4. https://plus.maths.org/content/os/issue4/puzzle/taxi/solution.
R Software Package
Lemon,J., Bolker, B., Oom, S., Klein, E., Rowlingson, B., Wickham, H., Tyagi,A., Eterradossi, O., Grothendieck, G., Toews, M., Kane, J., Cheetham, M.,Turner, R., Witthoft, C., Stander, J., Petzoldt, T., Duursma, R., Biancotto, E., Levy, O., Dutang, C., Solymos, P., Engelmann, R., Hecker, M., Steinbeck, F., Borchers, H., Singmann, H., Toal, T.,Ogle, D., Baral, D. and Groemping, U. (2017) plotrix: various plottingfunctions. R package. https://cran.r-project.org/web/packages/plotrix/index.html.
Open Peer Review
13th August 2018. Review of Erango, M., Frigessi, A. and Rosseland, L.A. (2018). A three minutes supine position test reveals higher risk of spinal anesthesia induced hypotension during cesarean delivery. An observational study. F1000 Research. https://f1000research.com/articles/7-1028/v1
Other academic activities
I take part in Schools, Public and Community Outreach.
I play the flute.
I lived and worked in Italy and can speak good Italian.