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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.
- Published on: 2010-07-06
- Original language: English
- Binding: Printed Access Code
Review
"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
About the Author
Roger Koenker is McKinley Professor of Economics and Professor of Statistics at the University of Illinois at Urbana-Champaign. From 1976 to 1983 he was a member of the technical staff at Bell Laboratories. He has held visiting positions at The University of Pennsylvania, Charles University, Prague, Nuffield College, Oxford, University College London and Australian National University. He is a Fellow of the Econometric Society.
Most helpful customer reviews
4 of 4 people found the following review helpful.
new views for modern data
By Jan Galkowski
Modern data are plentiful and, as always, complicated. Yet the demand for interpretations and explanations are ever more urgent. There's a pressure to do more in less time.
Quantile regression is based upon a reinterpretation of the least squares method, providing a flexible means of doing data analysis. Rather than seeing a dataset as a "signal contaminated with noise", it suggests all the effects recorded there are worthy of study, if only to understand processes which interfere with primary measurements.
In cases of complicated observations and datasets, it promises to serve as a powerful tool.
Prior to purchase, I recommend Koenker, Hallock, J.Econ.Perspectives 15(4), 143-156, Fall 2001, and especially Cade, Noon, Frontiers Ecol. Environ 2003, 1(8), 412-420 as previews.
I look forward to indulging myself with the text.
2 of 2 people found the following review helpful.
Great book - But severe typos in the Kindle edition at least.
By expateconomiste
This book is an important reference on quantile regressions. It gives an overview that papers will not easily give you. However, detailed proofs are usually only available in the published papers.
However, I bought the Kindle edition of the book, and there are numerous severe copyediting/typographic problems in the book. For instance, section 4.6.1 has an important sentence that never finishes. Somewhere else in the book the maths get jammed. I have not checked the print edition of the book, but these are severe problems that should have been eliminated with copyediting.
Otherwise, this book is crucial for anybody doing quantile regression analysis.
5 of 7 people found the following review helpful.
Resource for any economist
By D. G. Wiczer
QR is a fascinating and increasingly important tool for any economist (note that I leave of the "-trician"). Especially when we consider heterogenous agent models, the standard techniques of mean-regression seem comparatively mindless. Who better to teach the subject than the man who invented it? He's got an engaging voice and clear pen.
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