Model Selection (Wiley Series in Probability and Statistics - Applied Probability and Statistics Section)

The first work to deal exclusively with objective criteria for comparing statistical models. Using a simple framework, it outlines a general strategy for selecting a model and applies this strategy to develop methods useful for solving specific selection problems. Topics covered include histograms, univariate distributions, simple and multiple regression, the analysis of variance and covariance, the analysis of proportions and contingency tables, time series analysis, and spatial analysis.