Multivariate Statistical Modelling Based on Generalized Linear Models / Springer Series in Statistics (PDF)
(Sprache: Englisch)
Concerned with the use of generalised linear models for univariate and multivariate regression analysis, this is a detailed introductory survey of the subject, based on the analysis of real data drawn from a variety of subjects such as the biological...
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Concerned with the use of generalised linear models for univariate and multivariate regression analysis, this is a detailed introductory survey of the subject, based on the analysis of real data drawn from a variety of subjects such as the biological sciences, economics, and the social sciences. Where possible, technical details and proofs are deferred to an appendix in order to provide an accessible account for non-experts. Topics covered include: models for multi-categorical responses, model checking, time series and longitudinal data, random effects models, and state-space models. Throughout, 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, numerous researchers whose work relies on the use of these models will find this an invaluable account.
Bibliographische Angaben
- Autoren: Ludwig Fahrmeir , Gerhard Tutz
- 2013, 1994, 426 Seiten, Englisch
- Verlag: Springer, New York
- ISBN-10: 1489900101
- ISBN-13: 9781489900104
- Erscheinungsdatum: 11.11.2013
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- Grösse: 35 MB
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