Statistical Science


Professor Richard Chandler

PositionProfessor of Statistics
Phone (external)+44 (0)20 7679 1880
Phone (internal)41880
Personal webpagehttp://www.homepages.ucl.ac.uk/~ucakarc/
ThemesGeneral Theory and Methodology

* @ucl.ac.uk

Biographical Details

Richard is a Professor in the Department of Statistical Science at University College London, where he has worked since completing his PhD at UMIST in 1994. He is a Fellow of the Royal Statistical Society, member of the Bernoulli and International Environmetric Societies and an honorary member of the Institute of Atmospheric Physics in Beijing. He has served as Joint Editor for the Journal of the Royal Statistical Society, Series C (Applied Statistics), and led large multidisciplinary research projects focused on natural hazards, risk and uncertainty. He currently serves on the committees of the International Meeting series on Statistical Climatology and on the Bernoulli Society’s Committee on Probability and Statistics in the Physical Sciences.

Research Interests

Richard has extensive experience of developing and applying statistical methods for the environmental sciences. Particular interests include the analysis of time series and space-time data, with application areas including hydrology and the impacts of climate change. Other areas of interest include the assessment of uncertainty when interpreting model outputs.

Selected publications

  • Outhwaite, C.L., Gregory, R.D., Chandler, R.E., Collen B. and Isaac N.J.B (2020). Complex long-term biodiversity change among invertebrates, bryophytes and lichens. Nat Ecol Evol. doi: 10.1038/s41559-020-1111-z.
  • Barnes, C., C.M. Brierley and R.E. Chandler (2019). New approaches to postprocessing of multimodel ensemble forecasts. Q. J. R. Meteorol. Soc., 145, 3479-3498, doi: 10.1002/qj.3632.
  • Jesus, J. and R.E. Chandler (2017). Inference with the Whittle Likelihood: A Tractable Approach Using Estimating Functions. J. Time Ser. Anal., 38: 204-224. doi: 10.1111/jtsa.12225.
  • Chandler R.E. (2013). Exploiting strength, discounting weakness: combining information from multiple climate simulators. Phil Trans R Soc A 371: 20120388, doi: 10.1098/rsta.2012.0388.
  • Maraun, D., F. Wetterhall, A.M. Ireson, R. E. Chandler, E. J. Kendon, M. Widmann, S. Brienen, H.W. Rust, T. Sauter, M. Themeßl, V.K.C. Venema, K.P. Chun, C.M. Goodess, R.G. Jones, C. Onof, M. Vrac, and I. Thiele-Eich (2010). Precipitation downscaling under climate change - recent developments to bridge the gap between dynamical models and the end user. Reviews of Geophysics, 48, RG3003, 34pp. doi: 10.1029/2009RG000314.
  • Jesus, J. and R.E. Chandler (2011). Estimating functions and the generalized method of moments. Interface Focus, 1(6), 871-885, DOI: 10.1098/rsfs.2011.0057.
  • Chandler, R.E. and E.M. Scott (2011). Statistical Methods for Trend Detection and Analysis in the Environmental Sciences. Wiley, Chichester. Data sets and software available from here.
  • Chandler, R.E. and Bate, S. (2007). Inference for clustered data using the independence log-likelihood. Biometrika 94, pp. 167-183. doi:0.1093/biomet/asm015.
  • Yang, C., Chandler, R.E., Isham, V. and Wheater, H.S. (2005). Spatial-temporal rainfall simulation using Generalized Linear Models. Water Resources Research 41, doi:10.1029/2004WR003739.
  • Chandler, R.E. (2005). On the use of generalized linear models for interpreting climate variability. Environmetrics 16(7), pp. 699-715. doi:10.1002/env.731.