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Multivariate statistical modelling based on generalized linear models

Author: L Fahrmeir; Gerhard Tutz
Publisher: New York : Springer, ©2001.
Series: Springer series in statistics.
Edition/Format:   Print book : English : 2nd ed. / with contributions from Wolfgang HennevoglView all editions and formats
Summary:
"The authors give a detailed introductory survey of the subject based on the analysis of real data drawn from a variety of subjects, including the biological sciences, economics, and the social sciences. Technical details and proofs are deferred to an appendix in order to provide an accessible account for nonexperts. The appendix serves as a reference or brief tutorial for the concepts of the EM algorithm, numerical  Read more...
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Material Type: Internet resource
Document Type: Book, Internet Resource
All Authors / Contributors: L Fahrmeir; Gerhard Tutz
ISBN: 0387951873 9780387951874
OCLC Number: 45270370
Description: xxvi, 517 pages : illustrations ; 24 cm.
Contents: 1. Introduction --
2. Modelling and Analysis of Cross-Sectional Data: A Review of Univariate Generalized Linear Models --
3. Models for Multicategorical Responses: Multivariate Extensions of Generalized Linear Models --
4. Selecting and Checking Models --
5. Semi- and Nonparametric Approaches to Regression Analysis --
6. Fixed Parameter Models for Time Series and Longitudinal Data --
7. Random Effects Models --
8. State Space and Hidden Markov Models --
9. Survival Models --
A.1. Exponential Families and Generalized Linear Models --
A.2. Basic Ideas for Asymptotics --
A.3. EM Algorithm --
A.4. Numerical Integration --
A.5. Monte Carlo Methods --
B. Software for Fitting Generalized Linear Models and Extensions.
Series Title: Springer series in statistics.
Responsibility: Ludwig Fahrmeir, Gerhard Tutz.
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Abstract:

The book is aimed at applied statisticians, graduate students of statistics, and students and researchers with a strong interest in statistics and data analysis. This second edition is extensively  Read more...

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From the reviews of the second edition:TECHNOMETRICS"A 25% size increase in a very generous effort for a new edition of a statistics book. If you own and like the 1E, then a purchase of the 2E would Read more...

 
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   schema:reviewBody ""The authors give a detailed introductory survey of the subject based on the analysis of real data drawn from a variety of subjects, including the biological sciences, economics, and the social sciences. Technical details and proofs are deferred to an appendix in order to provide an accessible account for nonexperts. The appendix serves as a reference or brief tutorial for the concepts of the EM algorithm, numerical integration, MCMC, and others." "In the new edition, Bayesian concepts, which are of growing importance in statistics, are treated more extensively. The chapter on nonparametric and semiparametric generalized regression has been rewritten totally, random effects models now cover nonparametric maximum likelihood and fully Bayesian approaches, and state-space and hidden Markov models have been supplemented with an extension to models that can accommodate for spatial and spatiotemporal data." "The authors have taken great pains to discuss the underlying theoretical ideas in ways that relate well to the data at hand. As a result, this book is ideally suited for applied statisticians, graduate students of statistics, and students and researchers with a strong interest in statistics and data analysis from econometrics, biometrics, and the social sciences."--Jacket." ;
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