Quantile Regression

Business & Finance, Economics, Econometrics, Nonfiction, Science & Nature, Mathematics
Cover of the book Quantile Regression by Roger Koenker, Cambridge University Press
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Author: Roger Koenker ISBN: 9781107713833
Publisher: Cambridge University Press Publication: May 5, 2005
Imprint: Cambridge University Press Language: English
Author: Roger Koenker
ISBN: 9781107713833
Publisher: Cambridge University Press
Publication: May 5, 2005
Imprint: Cambridge University Press
Language: English

Quantile regression is gradually emerging as a unified statistical methodology for estimating models of conditional quantile functions. By complementing the exclusive focus of classical least squares regression on the conditional mean, quantile regression offers a systematic strategy for examining how covariates influence the location, scale and shape of the entire response distribution. This monograph is the first comprehensive treatment of the subject, encompassing models that are linear and nonlinear, parametric and nonparametric. The author has devoted more than 25 years of research to this topic. The methods in the analysis are illustrated with a variety of applications from economics, biology, ecology and finance. The treatment will find its core audiences in econometrics, statistics, and applied mathematics in addition to the disciplines cited above.

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Quantile regression is gradually emerging as a unified statistical methodology for estimating models of conditional quantile functions. By complementing the exclusive focus of classical least squares regression on the conditional mean, quantile regression offers a systematic strategy for examining how covariates influence the location, scale and shape of the entire response distribution. This monograph is the first comprehensive treatment of the subject, encompassing models that are linear and nonlinear, parametric and nonparametric. The author has devoted more than 25 years of research to this topic. The methods in the analysis are illustrated with a variety of applications from economics, biology, ecology and finance. The treatment will find its core audiences in econometrics, statistics, and applied mathematics in addition to the disciplines cited above.

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