Originally published in 1990, the first edition of Subset Selection in Regression filled a significant gap in the literature, and its critical and popular success has continued for more than a decade. Thoroughly revised to reflect progress in theory, methods, and computing power, the second edition promises to continue that tradition. The author ha

Introduction. Least-Squares Computations. Finding Subsets which Fit Well. Hypothesis Testing. How Many Variables? Estimation after Model Selection. Bayesian Methods. Conclusions.