Penalty, Shrinkage and Pretest Strategies : Variable Selection and Estimation

種類:

電子ブック

責任表示:

by S. Ejaz Ahmed

出版情報:

Cham : Springer International Publishing : Imprint: Springer, 2014

著者名:

• Ahmed, S. Ejaz
• SpringerLink (Online service)

シリーズ名:

SpringerBriefs in Statistics ;

ISBN:

9783319031491 [331903149X]    

注記:

The objective of this book is to compare the statistical properties of penalty and non-penalty estimation strategies for some popular models. Specifically, it considers the full model, submodel, penalty, pretest and shrinkage estimation techniques for three regression models before presenting the asymptotic properties of the non-penalty estimators and their asymptotic distributional efficiency comparisons. Further, the risk properties of the non-penalty estimators and penalty estimators are explored through a Monte Carlo simulation study. Showcasing examples based on real datasets, the book will be useful for students and applied researchers in a host of applied fields. The book’s level of presentation and style make it accessible to a broad audience. It offers clear, succinct expositions of each estimation strategy. More importantly, it clearly describes how to use each estimation strategy for the problem at hand. The book is largely self-contained, as are the individual chapters, so that anyone interest

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