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The Resource Multivariate statistical modelling based on generalized linear models, Ludwig Fahrmeir, Gerhard Tutz ; with contributions from Wolfgang Hennevogl

Multivariate statistical modelling based on generalized linear models, Ludwig Fahrmeir, Gerhard Tutz ; with contributions from Wolfgang Hennevogl

Label
Multivariate statistical modelling based on generalized linear models
Title
Multivariate statistical modelling based on generalized linear models
Statement of responsibility
Ludwig Fahrmeir, Gerhard Tutz ; with contributions from Wolfgang Hennevogl
Creator
Contributor
Subject
Language
eng
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 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
  • "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."--BOOK JACKET
Member of
Cataloging source
DLC
http://library.link/vocab/creatorName
Fahrmeir, L
Dewey number
519.5/38
Illustrations
illustrations
Index
index present
LC call number
QA278
LC item number
.F34 2001
Literary form
non fiction
Nature of contents
bibliography
http://library.link/vocab/relatedWorkOrContributorName
Tutz, Gerhard
Series statement
Springer series in statistics
http://library.link/vocab/subjectName
  • Multivariate analysis
  • Linear models (Statistics)
Label
Multivariate statistical modelling based on generalized linear models, Ludwig Fahrmeir, Gerhard Tutz ; with contributions from Wolfgang Hennevogl
Instantiates
Publication
Bibliography note
Includes bibliographical references (pages 467-504) and indexes
Carrier category
volume
Carrier category code
nc
Carrier MARC source
rdacarrier
Content category
text
Content type code
txt
Content type MARC source
rdacontent
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
Control code
45270370
Dimensions
25 cm
Edition
2nd ed.
Extent
xxvi, 517 pages
Isbn
9780387951874
Isbn Type
(alk. paper)
Lccn
00052275
Media category
unmediated
Media MARC source
rdamedia
Media type code
n
Other physical details
illustrations
Label
Multivariate statistical modelling based on generalized linear models, Ludwig Fahrmeir, Gerhard Tutz ; with contributions from Wolfgang Hennevogl
Publication
Bibliography note
Includes bibliographical references (pages 467-504) and indexes
Carrier category
volume
Carrier category code
nc
Carrier MARC source
rdacarrier
Content category
text
Content type code
txt
Content type MARC source
rdacontent
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
Control code
45270370
Dimensions
25 cm
Edition
2nd ed.
Extent
xxvi, 517 pages
Isbn
9780387951874
Isbn Type
(alk. paper)
Lccn
00052275
Media category
unmediated
Media MARC source
rdamedia
Media type code
n
Other physical details
illustrations

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