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Field name	Details
Dewey Class	519.2
Title	Multivariate Statistical Modelling Based on Generalized Linear Models ([EBook] /) / by Ludwig Fahrmeir, Gerhard Tutz.
Author	Fahrmeir, Ludwig
Added Personal Name	Tutz, Gerhard author.
Other name(s)	SpringerLink (Online service)
Edition statement	Second Edition.
Publication	New York, NY : : Springer New York : : Imprint: Springer, , 2001.
Physical Details	XXVI, 518 p. : online resource.
Series	Springer Series in Statistics 0172-7397
ISBN	9781475734546
Summary Note	Since our first edition of this book, many developments in statistical mod elling based on generalized linear models have been published, and our primary aim is to bring the book up to date. Naturally, the choice of these recent developments reflects our own teaching and research interests. The new organization parallels that of the first edition. We try to motiv ate and illustrate concepts with examples using real data, and most data sets are available on http:/ fwww. stat. uni-muenchen. de/welcome_e. html, with a link to data archive. We could not treat all recent developments in the main text, and in such cases we point to references at the end of each chapter. Many changes will be found in several sections, especially with those connected to Bayesian concepts. For example, the treatment of marginal models in Chapter 3 is now current and state-of-the-art. The coverage of nonparametric and semiparametric generalized regression in Chapter 5 is completely rewritten with a shift of emphasis to linear bases, as well as new sections on local smoothing approaches and Bayesian inference. Chapter 6 now incorporates developments in parametric modelling of both time series and longitudinal data. Additionally, random effect models in Chapter 7 now cover nonparametric maximum likelihood and a new section on fully Bayesian approaches. The modifications and extensions in Chapter 8 reflect the rapid development in state space and hidden Markov models.:
Contents note	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. -- 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 -- Author Index.
System details note	Online access to this digital book is restricted to subscription institutions through IP address (only for SISSA internal users)
Internet Site	http://dx.doi.org/10.1007/978-1-4757-3454-6
Links to Related Works	Subject References: Mathematical Modeling and Industrial Mathematics . Mathematical models . Mathematics . Probabilities . Probability theory and stochastic processes . Statistical Theory and Methods . Statistics . Statistics for Business/Economics/Mathematical Finance/Insurance . Statistics for Life Sciences, Medicine, Health Sciences . Statistics, general . Authors: Fahrmeir, Ludwig . Tutz, Gerhard . Corporate Authors: SpringerLink (Online service) . Series: Springer Series in Statistics . Classification: 519.2 .

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Multivariate Statistical Modelling Based on Generalized Linear Models

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