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Regression And Time Series Model Selection
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.
Time Series Analysis and Its Applications
The second edition marks a substantial change to the ?rst edition. P- haps the most signi?cant change is the introduction of examples based on the freeware R package. The package, which runs on most operating systems, can be downloaded from The Comprehensive R Archive Network (CRAN) at http://cran. r-project. org/ or any one of its mirrors. Readers who have experience with the S-PLUS R package will have no problem working with R. For novices, R installs some help manuals, and CRAN supplies links to contributed tutorials such as R for Beginners. In our examples, we assume the reader has downloaded and installed R and has downloaded the nec- sary data ?les. The data ?les can be downloaded from...
American Journal of Veterinary Research
Volumes for 1956- include selected papers from the proceedings of the American Veterinary Medical Association.
AMSTAT News
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Technometrics
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