Professor Li's research interests concern some areas of statistics, including finite mixture model, asymptotic theory, empirical likelihood, inference with constraints, experimental design, and smoothing technique.
Currently he is particularly interested in these topics:
- hypothesistesting in finite mixture models;
- inference with constraints such asexponential tilting and ordering constraints;
- construction of optimalfractional factorial designs and robust designs;
- smoothing technique with application to brain imaging data analysis.
Professor Li received his PhD in statistics in 2007 from the University of Waterloo, and then spent six months at the University of British Columbia as a postdoctoral fellow (2008). He worked as the assistant professor at the University of Alberta for three and half years (2008-2011). He joined the University of Waterloo in January 2012. He serves as an associate editor for the Canadian Journal of Statistics.
- Chen, J., Li, P. and Fu, Y. (2012). Inference on the order of a normal mixture. Journal of the American Statistical Association, 107, 1096-1105.
- Li, P. and Qin, J. (2011). A new nuisance parameter elimination method with application to unordered homologous chromosome pairs problem. Journal of the American Statistical Association, 106, 1476-1484.
- Li, P. and Wiens, D. (2011). Robustness of design in dose-response Studies. Journal of the Royal Statistical Society: Series B, 73, 215-238.
- Li, P. and Chen, J. (2010). Testing the order of a finite mixture model. Journal of the American Statistical Association, 105, 1084-1092.
- Chen, J. and Li, P. (2009). Hypothesis test for normal mixture models: the EM approach. The Annals of Statistics, 37, 2523-2542.
- Li, P., Chen, J. and Marriott, P. (2009). Non-finite Fisher information and homogeneity: the EM approach. Biometrika, 96, 411-42.