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关键词：
Analyzing Categorical Data
书目信息
ISBN：
9780387007496（13位）
中图分类号：
O1
杜威分类号：
中文译名：
分类数据分析
作者：
Simonoff
编者：
语种：
English
出版信息
出版社：
Springer
出版地：
出版年：
2003
版本：
版本类型：
原版
丛书题名：
Springer Texts in Statistics
卷期：
文献信息
关键词：
Statistics
前言：
摘要：
内容简介：
Categorical data arise often in many fields, including biometrics, economics, management, manufacturing, marketing, psychology, and sociology. This book provides an introduction to the analysis of such data. The coverage is broad, using the loglinear Poisson regression model and logistic binomial regression models as the primary engines for methodology. Topics covered include count regression models, such as Poisson, negative binomial, zero-inflated, and zero-truncated models; loglinear models for two-dimensional and multidimensional contingency tables, including for square tables and tables with ordered categories; and regression models for two-category (binary) and multiple-category target variables, such as logistic and proportional odds models. All methods are illustrated with analyses of real data examples, many from recent subject area journal articles. These analyses are highlighted in the text, and are more detailed than is typical, providing discussion of the con text and background of the problem, model checking, and scientific implications. Almost 200 exercises are provided, many also based on recent subject area literature. Data sets and computer code are available at a web site devoted to the text. Jeffrey S. Simonoff is Professor of Statistics at New York University. He is author of Smoothing Methods in Statistics and coauthor of a Casebook for a First Course in Statistics and Data Analysis, as well as numerous articles in scholarly journals. He is a Fellow of the American Statistical Association, and an Elected Member of the International Statistical Institute.
目次：
附录：
全文链接：
读者对象：
grad.
实体信息
页码：
装帧：
hard
尺寸：
其它形态细节：
其它信息
原价：
EUR
84.9500
原版ISBN：
其它ISBN：
图书特色：
书评：
扩展信息
Isbn：
0387007490
issue：
2006JC01
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