Mark L. Reed III Distinguished Professor
Richard L. Smith is Mark L. Reed III Distinguished Professor of Statistics and Professor of Biostatistics in the University of North Carolina, Chapel Hill. From 2010-2017 he was also Director of the Statistical and Applied Mathematical Sciences Institute, a Mathematical Sciences Institute supported by the National Science Foundation, and he will continue (through June 2018) as Associate Director of SAMSI. He obtained his PhD from Cornell University and previously held academic positions at Imperial College (London), the University of Surrey (Guildford, England) and Cambridge University. His main research interest is environmental statistics and associated areas of methodological research such as spatial statistics, time series analysis and extreme value theory. He is particularly interested in statistical aspects of climate change research, and in air pollution including its health effects. He is a Fellow of the American Statistical Association and the Institute of Mathematical Statistics, an Elected Member of the International Statistical Institute, and has won the Guy Medal in Silver of the Royal Statistical Society, and the Distinguished Achievement Medal of the Section on Statistics and the Environment, American Statistical Association. In 2004 he was the J. Stuart Hunter Lecturer of The International Environmetrics Society (TIES). He is also a Chartered Statistician of the Royal Statistical Society.
Young, S.S., Lopiano, K. and Smith, R.L. (2017), Air quality and acute deaths in California, 2000-2012. To appear in Regulatory Toxicology and Pharmacology .
Katzfuss, M., Hammerling, D. and Smith, R.L. (2017), A Bayesian hierarchical model for climate change detection and attribution. Geophys. Res. Lett., 44, 1-9, doi:10.1002/2017GL073688
Erhardt, R.J., Band, L.E., Smith, R.L. and Lopes, B.J. (2015), Statistical downscaling of precipitation on a spatially dependent network using a regional climate model. Stochastic Environmental Research and Risk Assessment, Volume 29, Number 7, pp 1835-1849, DOI 10.1007/s00477-014-0988-y.
Hammerling, D., Cefalu, M., Cisewski, J., Dominici, F., Parmigiani, G., Paulson, C. and Smith, R.L. (2014), Completing the Results of the 2013 Boston Marathon.
PLoS ONE 9(4): e93800.
Craigmile, P.F., Guttorp, P., Lund, R., Smith, R.L., Thorne, P.W. and Arndt, D. (2014), Warm streaks in the U.S. temperature record: What are the chances? Journal of Geophysical Research: Atmospheres. Published online : 19 MAY 2014, DOI: 10.1002/2013JD021446
Erhardt, R.J. and Smith, R.L. (2014), Weather derivative risk measures for extreme events. North American Actuarial Journal, DOI: 10.1080/10920277.2014.910472
Smith, R.L., Powers, S. and Cisewski, J. (2014), Qualifying times for the Boston marathon. Chance 27 (3), 25-33.
Teaching Webpages (Current):
Fall SAMSI class on Statistical Methods for Climate Research
Conference Talks and Seminar Presentations
Boston Marathon project
California Air Pollution project
Short Course in Kolkata, March 2015
Lectures on Extreme Value Theory given at North Carolina State University, 2015
Project on Marathon Times and Ages
Teaching Webpages (Older):
STOR 664: Applied Statistics I, Fall 2009.
STOR 940: SAMSI course on Spatial Epidemiology, Fall 2009.
STOR 151 (Basic Concepts of Statistics), Spring 2010.
STOR 654 (Time Series and Multivariate Analysis), Fall 2008.
STOR 890 (Environmental Statistics), Spring 2009.
STOR 356, Spring 2008.
Statistics 174: Applied Statistics I, Fall 2004
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Updated June 22, 2017