Regression for Categorical Data: 34 (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 34) - Hardcover

Tutz, Gerhard

Hardcover

ISBN 10: 1107009650 ISBN 13: 9781107009653

Verlag: Cambridge University Press, 2011

Inhaltsangabe

This book introduces basic and advanced concepts of categorical regression with a focus on the structuring constituents of regression and recent developments in flexible and high-dimensional regression. Among the topics treated are nonparametric regression; the hurdle model and zero-inflated regression models for count data; and non-standard tree-based ensemble methods.

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Críticas:

"Regression for Categorical Data is a well-written and nicely organized book. It focuses on the regression analysis of categorical data, including both binary and count data, and introduced up-to-date developments in the field."
Xia Wang, Mathematical Reviews

Reseña del editor:

This book introduces basic and advanced concepts of categorical regression with a focus on the structuring constituents of regression, including regularization techniques to structure predictors. In addition to standard methods such as the logit and probit model and extensions to multivariate settings, the author presents more recent developments in flexible and high-dimensional regression, which allow weakening of assumptions on the structuring of the predictor and yield fits that are closer to the data. A generalized linear model is used as a unifying framework whenever possible in particular parametric models that are treated within this framework. Many topics not normally included in books on categorical data analysis are treated here, such as nonparametric regression; selection of predictors by regularized estimation procedures; ternative models like the hurdle model and zero-inflated regression models for count data; and non-standard tree-based ensemble methods. The book is accompanied by an R package that contains data sets and code for all the examples.

Über diese Auflage

• Verlag: Cambridge University Press
• Erscheinungsdatum: 2011
• ISBN 10: 1107009650
• ISBN 13: 9781107009653
• Einband: Tapa dura
• Anzahl der Seiten: 572