Regression for categorical data (Record no. 201569)

000 -LEADER
fixed length control field 02555 a2200217 4500
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 151103b2012 xxu||||| |||| 00| 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 1107009650
022 ## - INTERNATIONAL STANDARD SERIAL NUMBER
International Standard Serial Number 9780511842061
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 519.536
Item number T8R3
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Tutz, Gerhard
9 (RLIN) 324058
245 ## - TITLE STATEMENT
Title Regression for categorical data
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc Cambridge
Name of publisher, distributor, etc Cambridge University Press
Date of publication, distribution, etc 2012
300 ## - PHYSICAL DESCRIPTION
Extent x, 561 p.
440 ## - SERIES STATEMENT/ADDED ENTRY--TITLE
Title Cambridge Series in Statistical and Probabilistic Mathematics; 34
9 (RLIN) 323606
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc Table of contents: <br/><br/>1. Introduction <br/>2. Binary Regression: The Logit Model <br/>3. Generalized Linear Models <br/>4. Modeling of Binary Data <br/>5. Alternative Binary Regression Models <br/>6. Regularization and Variable Selection for Parametric Models <br/>7. Regression Analysis of Count Data <br/>8. Multinomial Response Models <br/>9. Ordinal Response Models <br/>10. Semi- and Non-Parametric Generalized Regression <br/>11. Tree-Based Methods <br/>12. The Analysis of Contingency Tables: Log-Linear and Graphical Models <br/>13. Multivariate Response Models <br/>14. Random Effects Models and Finite Mixtures <br/>15. Prediction and Classification <br/><br/>
520 ## - SUMMARY, ETC.
Summary, etc 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, which provide excellent tools for prediction and the handling of both nominal and ordered categorical predictors. The book is accompanied an R package that contains data sets and code for all the examples.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Statistical theory and methods
9 (RLIN) 323603
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Statistical and probabilistic mathematics
9 (RLIN) 323649
856 ## - ELECTRONIC LOCATION AND ACCESS
Materials specified E-Book
Uniform Resource Identifier <a href="http://ebooks.cambridge.org/ebook.jsf?bid=CBO9780511842061">http://ebooks.cambridge.org/ebook.jsf?bid=CBO9780511842061</a>
Access method Unlimited (Internet)
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme
Item type eBooks
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Collection code Permanent location Current location Shelving location Date acquired Source of acquisition Cost, normal purchase price Full call number Barcode Date last seen Cost, replacement price Koha item type
          Non-fiction Vikram Sarabhai Library Vikram Sarabhai Library Electronic Resources 03/11/2015 Cambridge University Press (I) Pvt. Ltd. 11585.93 519.536 T8R3 ER000498 03/11/2015 13630.50 eBooks

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