McQuarrie, A.D.R., Tsai, C.-L. Regression and Time Series Model Selection

Singapore, World Scientific Pub Co Inc, 1998. — 455 p.
ISBN10: 981023242X
ISBN13: 978-9810232429Describes procedures for selecting a model from a large set of competing statistical models. The text includes: model-selection techniques for univariate and multivariate regression models; univariate and multivariate autoregressive models; nonparametric (including wavelets) and semi-parametric 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 range of models.The Univariate Regression Model
The Univariate Autoregressive Model
The Multivariate Regression Model
The Vector Autoregressive Model
Cross-Validation and the Bootstrap
Robust Regression and Quasi-Likelihood
Nonparametric Regression and Wavelets
Simulations and Examples