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Titre :
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Regression and time series model selection
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Auteurs :
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A. Mac Quarrie ;
C. Tsai
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Type de document :
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ouvrage
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Editeur :
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River Edge, USA : World scientific publishing, 1998
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ISBN/ISSN/EAN :
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981-02-3242-X
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Format :
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455 p.
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Langues:
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= Anglais
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Catégories :
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Informatique, statistique, mathématique
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Mots-clés:
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MODELE
;
MODELISATION
;
ANALYSE STATISTIQUE
;
SELECTION
;
SIMULATION
;
METHODOLOGIE
;
REGRESSION
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Résumé :
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This book describes procedures for selecting a model from a large set of competing statistical models. It includes model selection techniques for univariate and multivariate regression models, univariate and multivariate autoregressive models, nonparametric (including wavelets) and semiparametric regression models, and quasi-likelihood and robust regression models. Information-based model selection criteria are discussed, and small sample and asymptotic properties are presented. It also provides examples and large scale simulation studies comparing the performances of information-based model selection criteria, bootstrapping, and cross-validation selection methods over a wide range of models. It includes the following chapters : Introduction to model selection. The univariate regression model. The univariate autoregressive model. The multivariate regression model. The vector autoregressive model. The cross-validation and bootstrap. Robust and quasi-likelihood model selections. Nonparametric regressions and wavelets. Simulations and case studies.
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