Improving efficiency by shrinkage : the James-Stein and ridge regression estimators

Autor: Gruber, Marvin H. J.
Rok: c1998
ISBN: 9780824701567
OKCZID: 110164210

Citace (dle ČSN ISO 690):
GRUBER, Marvin H. J. Improving efficiency by shrinkage: the James-Stein and ridge regression estimators. New York: Dekker, c1998. xii, 632 s. Statistics, vol. 156.

Anotace

This well-targeted reference/text 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 both analytically and numerically and includes Mathematica and Maple programs used in numerical comparison! Self-contained for practitioners and students with a background in linear models, Improving Efficiency by Shrinkage provides a historical survey of a vast amount of literature on the subject demonstrates why, when, and where ridge regression estimators are advantageous furnishes a proof of the inadmissibility of the James-Stein estimator illustrates how shrinkage estimators solve applied problems addresses practical issues in the study of ridge estimators contrasts efficiencies with the least square estimator shows how to improve the efficiency of James-Stein estimators by using positive parts and more! With nearly 1300 equations, bibliographic citations, and figures, Improving Efficiency by Shrinkage is an outstanding reference for applied statisticians, engineers, econometricians, sociologists, psychologists, data analysts, biometricians, and medical researchers and an excellent text for graduate-level courses in regression, linear models, and econometrics as well as seminars in statistics.

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