Regression for Categorical Data (Record no. 7303)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 02074nam a2200277Ia 4500 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | OSt |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20251119101414.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 220909b |||||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9781107009653 |
| 037 ## - SOURCE OF ACQUISITION | |
| Terms of availability | Textbook |
| 040 ## - CATALOGING SOURCE | |
| Original cataloging agency | CSL |
| Language of cataloging | eng |
| Transcribing agency | CSL |
| 041 ## - LANGUAGE CODE | |
| Language code of text/sound track or separate title | eng |
| 084 ## - COLON CLASSIFICATION NUMBER | |
| Classification number | B284 Q2 TB |
| Assigning agency | CSL |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Tutz, Gerhard |
| Relator term | author |
| 9 (RLIN) | 852160 |
| 245 #0 - TITLE STATEMENT | |
| Title | Regression for Categorical Data |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
| Place of publication, distribution, etc. | Cambridge : |
| Name of publisher, distributor, etc. | Cambridge , |
| Date of publication, distribution, etc. | 2012 . |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | x, 561p. |
| 490 ## - SERIES STATEMENT | |
| Series statement | Cambridge series in statistical and probabilistic mathematics |
| 500 ## - GENERAL NOTE | |
| General note | Included Bibliography 513-544p.; Author index 545-553p.; Subject index 554-561p. |
| 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 entry element | Categorical data. |
| 9 (RLIN) | 852161 |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Regression analysis. |
| 9 (RLIN) | 852162 |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Mathematics. |
| 9 (RLIN) | 852163 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Classification part | B284 Q2 TB |
| Koha item type | Textbook |
| Source of classification or shelving scheme | Colon Classification (CC) |
| Suppress in OPAC | No |
| Withdrawn status | Lost status | Source of classification or shelving scheme | Damaged status | Not for loan | Home library | Current library | Date acquired | Total Checkouts | Full call number | Barcode | Date last seen | Price effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Colon Classification (CC) | Central Science Library | Central Science Library | 2012-06-28 | B284 Q2 TB | SL1558518 | 2022-09-12 | 2022-09-12 | Textbook |