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Regression And Time Series Model Selection - Chih-ling Tsai

Regression And Time Series Model Selection

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This important 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. The book 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.

Preface
List of Tables
Introductionp. 1
The Univariate Regression Modelp. 15
The Univariate Autoregressive Modelp. 89
The Multivariate Regression Modelp. 141
The Vector Autoregressive Modelp. 199
Cross-validation and the Bootstrapp. 251
Robust Regression and Quasi-likelihoodp. 293
Nonparametric Regression and Waveletsp. 329
Simulations and Examplesp. 365
Referencesp. 430
Author Indexp. 440
Indexp. 445
Table of Contents provided by Blackwell. All Rights Reserved.

ISBN: 9789810232429
ISBN-10: 981023242X
Audience: Professional
Format: Hardcover
Language: English
Number Of Pages: 480
Published: 1st August 1998
Country of Publication: SG
Dimensions (cm): 22.86 x 16.51  x 3.18
Weight (kg): 0.77