Improving Efficiency by Shrinkage The James--Stein and Ridge Regression Estimators Statistics: A Series of Textbooks and Monographs Series

Offers a treatment of different kinds of James-Stein and ridge regression estimators from a frequentist and Bayesian point of view. The book explains and compares estimators analytically as well as numerically and includes Mathematica and Maple programs used in numerical comparison.;College or university bookshops may order five or more copies at a special student rate, available on request.

Introduction to shrinkage estimators: the Stein paradox; the ridge estimators of Hoerl and Kennard. Estimation for a single linear model: the James-Stein estimator for a single model; ridge estimators from different general points of view; improving the James-Stein estimator - the positive parts. Other linear model setups: the simultaneous estimation problem; precision of individual estimators; the multivariate model; other linear model setups.

Professional

Marvin Gruber

Offers a unified treatment of different kinds of James-Stein and ridge regression estimators from a frequentist and Bayesian point of view. Explains and compares estimators analytically as well as numerically and includes Mathematics and Maple programs used in numerical comparison.