Choosing a model is central to all statistical work with data. We have seen rapid advances in model fitting and in the theoretical understanding of model selection, yet this book is the first to synthesize research and practice from this active field. Model choice criteria are explained, discussed and compared, including the AIC, BIC, DIC and FIC. The uncertainties involved with model selection are tackled with discussions of frequent and Bayesian methods; model averaging schemes are presented. Real-data examples are complemented by derivations providing deeper insight into the methodology, and instructive exercises build familiarity with the methods. The companion website features Data sets and R-code.

Author: Gerda Claeskens, Nils Lid Hjort
Binding Type: Hardcover
Publisher: Cambridge University Press
Published: 07/28/2008
Series: Cambridge Series in Statistical and Probabilistic Mathematics #27
Pages: 332
Weight: 1.9lbs
Size: 10.10h x 6.90w x 1.00d
ISBN: 9780521852258


Review Citation(s):
Scitech Book News 12/01/2008 pg. 37

About the Author
Claeskens, Gerda: - Gerda Claeskens is Professor in the OR and Business Statistics and Leuven Statistics Research Center at the Catholic University of Leuven, Belgium.Hjort, Nils Lid: - Nils Lid Hjort is Professor of Mathematical Statistics in the Department of Mathematics at the University of Oslo.