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Mathematics Confidence Intervals in Generalized Regression Models (Statistics: Textbooks and Monographs)
Posted on 2010-04-13
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Author: Esa Uusipaikka
Publisher: Chapman & Hall/CRC (2008) Binding: Hardcover, 328 pages pricer: $89.95 ISBN-10: 1420060279 editorialreviews A Cohesive Approach to Regression Models Confidence Intervals in Generalized Regression Models introduces a unified representation¡ªthe generalized regression model (GRM)¡ªof various types of regression models. It also uses a likelihood-based approach for performing statistical inference from statistical evidence consisting of data and its statistical model. Provides a Large Collection of Models The book encompasses a number of different regression models, from very simple to more complex ones. It covers the general linear model (GLM), nonlinear regression model, generalized linear model (GLIM), logistic regression model, Poisson regression model, multinomial regression model, and Cox regression model. The author also explains methods of constructing confidence regions, profile likelihood-based confidence intervals, and likelihood ratio tests. Uses Statistical Inference Package to Make Inferences on Real-Valued Parameter Functions Offering software that helps with statistical analyses, this book focuses on producing statistical inferences for data modeled by GRMs. It contains numerical and graphical results while providing the code online.
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