Quantile Regression

Quantile Regression

Quantile regression is gradually emerging as a unified statistical methodology for estimating models of conditional quantile functions. This monograph is the first comprehensive treatment of the subject, encompassing models that are linear and nonlinear, parametric and nonparametric. Roger Koenker has devoted more than 25 years of research to the topic. The methods in his analysis are illustrated with a variety of applications from economics, biology, ecology and finance and will target audiences in econometrics, statistics, and applied mathematics in addition to the disciplines cited above. Author resource page: http://www.econ.uiuc.edu/~roger/research/rq/rq.html

Roger Koenker is the winner of the 2010 Emanuel and Carol Parzen Prize for Statistical Innovation, awarded by the the Department of Statistics at Texas A&M University.


"Roger Koenker has a profound knowledge of econometrics, linear and non-linear programming, statistics and computational statistics, and a strong intuition, combined with a sense for practical problems. As a result, this excellent book combines all of these above aspects and covers a broad spectrum, from practical applications to the weak convergence of probability measures through examples on maximum daily temperatures to Choquet capacities...this book should definitely be on every statistician's and econometrician's shelf."
Jana Jureckova, Journal of the American Statistical Association

"The author is one [of] the "fathers" of quantile regression. He has substantially contributed to the theoretical as well as the applied development of the field. The book is well written... It provides useful information for statisticians and econometricians, and it can certainly serve as a reference book."
M. Huskova, Mathematical Reviews