Extended linear empirical Bayes estimation

    Comments

    Authors: contact us about adding a copy of your work at STARS@ucf.edu

    Keywords

    empirical Bayes; linear approximation; MODELS; Statistics & Probability

    Abstract

    In this paper, the linear empirical Bayes estimation method, which is based on approximation of the Bayes estimator by a linear function, is generalized to an extended linear empirical Bayes estimation technique which represents the Bayes estimator by a series of algebraic polynomials. The extended linear empirical Bayes estimators are elaborated in the case of a location or a scale parameter. The theory is illustrated by examples of its application to the normal distribution with a location parameter and the gamma distribution with a scale parameter. The linear and the extended linear empirical Bayes estimators are constructed in these two cases and, then, studied numerically via Monte Carlo simulations. The simulations show that the extended linear empirical Bayes estimators have better convergence rates than the traditional linear empirical Bayes estimators.

    Journal Title

    Communications in Statistics-Theory and Methods

    Volume

    29

    Issue/Number

    3

    Publication Date

    1-1-2000

    Document Type

    Article

    Language

    English

    First Page

    579

    Last Page

    592

    WOS Identifier

    WOS:000085700300007

    ISSN

    0361-0926

    Share

    COinS