Quantile Regression

Quantile regression, introduced by Koenker and Bassett (1978), has gradually developed into a comprehensive approach to the statistical analysis of linear and nonlinear response models. By supplementing the exclusive focus of least-squares-based methods on the estimation of conditional mean functions with a general technique for estimating conditional quantile functions, they have greatly expanded the flexibility of both parametric and non-parametric statistical methods. At present, however, the research describing these methods is widely scattered throughout the statistics and econometrics literature. In collaboration with Professor Roger Koenker, Department of Economics, University of Illinois, Professor Portnoy will prepare a monograph which will provide a systematic treatment of this literature. In conjunction with work on the monograph, they will continue their research efforts on related topics including nonparametric estimation of conditional quantile functions, statistical inference in quantile regression and applications to time-series and multivariate analysis.