Roger W. Koenker
Quantile regression, introduced in 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, the flexibility of both parametric and non-parametric statistical methods has greatly expanded. At present, however, the research describing these methods is widely scattered throughout the statistics and econometrics literature. In collaboration with Professor Stephen Portnoy, Department of Statistics, University of Illinois, Professor Koenker's monographs will provide a systematic treatment of this literature.
In conjunction with work on the monograph, work will continue on 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.