Adrian Bowman

School of Mathematics and Statistics University Gardens University of Glasgow GLASGOW G12 8QQ Phone:   0141 330 4046 Fax:       0141 330 4814 E-mail: adrian.bowman@glasgow.ac.uk

Research Interests

Selected publications and associated software.

• Bowman, A.W. & Azzalini, A.  (1997). Applied Smoothing Techniques for Data Analysis.  OUP.   A suite of R functions and scripts known as the sm package is also freely available in conjunction with the book.
• Bowman, A.W. & Wright, E. (1998). Graphical exploration of covariate effects on survival data through nonparametric quantile curves. Biometrics 56, 563-570. (S-Plus software.)
• Diblasi, A. & Bowman, A.W. (2001). On the use of the variogram for checking independence in a Gaussian spatial process.  Biometrics 57, 211-218. (S-Plus software.) 
• McMullan, A., Bowman, A.W. & Scott, E.M. (2003).  Non-linear and nonparametric modelling of seasonal environmental data. Computational Statistics 18, 167-183.
• Bowman, A.W. and Azzalini, A. (2003).  Computational aspects of nonparametric smoothing with illustrations from the sm library. Computational Statistics and Data Analysis  42, 545-56.
• Bock, M. & Bowman, A.W.  (2006).  On the measurement and analysis of asymmetry with applications to facial modelling. Applied Statistics  55, 77-91.
• Giannitrapani, M., Bowman, A.W., Scott, E.M. & Smith, R. (2005).   Sulphur dioxide in Europe: the relationship between emissions and measured concentrations. Atmospheric Environment, 40, 2524-2532.
• Bowman, A.W. & Bock, M. (2006). Exploring variation in three-dimensional shape data. J.Comp.Graph.Stat., 15, 524-541. (software)
• Bowman, A.W., Crawford, E.   Bowman, R.W. (2006). rpanel: making graphs move with tcltk. R News; 6, issue 4. (pdf; software)
• Bowman, A.W.  (2007).  Comparing nonparametric surfaces. Statistical Modelling; 6, 1-21. (software)
• Giannitrapani, M., Bowman, A.W., Scott, E.M. & Smith, R. (2007).  Temporal analysis of spatial covariance of SO2 in Europe from 1990 to 2001. Environmetrics; to appear.
• Bowman, A.W., Pope, A. & Ismail, B. (2007).   Detecting discontinuities in nonparametric regression curves and surfaces. Statistics and Computing; 16, 377-390.
• Bock, M., Bowman, A.W. & Ismail, B. (2007).  Estimation and inference for error variance in bivariate nonparametric regression. Statistics and Computing; to appear. (software)
• Ferguson, C.A., Bowman, A.W., Scott, E.M. & Carvalho. L. (2007).   Model comparson for a complex ecological system. J.Roy.Statist.Soc., Series A; to appear.
• Bowman, A.W., Crawford, E., Alexander, G. & Bowman, R.W. (2006).   rpanel: simple interactive controls for R functions using the tcltk package. Journal of Statistical Software 17, issue 9. (pdf; software)

• Giannitrapani, M., Bowman, A.W., & Scott, E.M. (2005).   Additive models for correlated data with applications to air pollution monitoring. (pdf)
• McMullan, A., Bowman, A.W. & Scott, E.M. (2006).   Water quality in the River Clyde: a case study of additive and interaction models. (pdf)
• Barry, S.J.E. & Bowman, A.W. (2006).   Linear mixed models for longitudinal shape data with applications to facial modelling. (pdf)
• Ferguson, C.A. & Bowman, A.W. & Scott, E.M. & Carvalho, L. (2006).   Multivariate varying-coefficient models for ecological systems. (pdf)
• Ferguson, C.A., Carvalho, L., Scott, E.M., Bowman, A.W. & Kirika, A. (2006).   Assessing ecological responses to environmental change using statistical models. (pdf)
• Bowman, A.W., Giannitrapani, M. & Scott, E.M. (2007).   Spatiotemporal smoothing and and sulphur dioxide trends over Europe. (pdf; supporting file)
• O'Donnell, D., Bowman, A.W., Scott, E.M. & Hallard, M. (2009).   Stream Distance Based Prediction on River Networks. (pdf)

Teaching related projects

The rpanel package provides a set of simple interactive controls for R functions which are particularly useful in creating dynamic graphics. The package is intended for general use but there is a particularly strong application in a teaching context. The web page for the project gives a variety of examples.

The Department of Statistics houses the Glasgow branch of the Higher Education Academy MSOR network.  The Glasgow activity provides information on, and resources for, the use of technology in the teaching and learning of statistics.

The STEPS project was created by a consortium of eight UK university departments who developed problem-based learning materials in Statistics, delivered on the computer.

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