Model selection and model averaging
By: Gerda Claeskens.
Series: Cambridge series in statistical and probabilistic mathematics -- 27
Publisher: Cambridge university press; Cambridge University Press
Published: 2008
Place of publication: Cambridge; New York
Language: eng
Number of pages: 332
ISBN-13: 9780521852258
Subjects: Mathematical models -- Research; Mathematical statistics -- Research; Bayesian statistical decision theory
Description: Given a data set, you can fit thousands of models at the push of a button, but how do you choose the best? With so many candidate models, overfitting is a real danger. Is the monkey who typed Hamlet actually a good writer? 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 frequentist 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.
Notes: Includes bibliographical references and indexes.