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Biometrika 1972 59(2):361-368; doi:10.1093/biomet/59.2.361
© 1972 by Biometrika Trust
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A continuous empirical Bayes smoothing technique

G. KEMBLE BENNETT and H. F. MARTZ

Virginia Polytechnic Institute and State University
Texas Tech University

Maritz (1966) and Lemon & Krutchkoff (1969) each describe discrete empirical Bayes smoothing techniques. These techniques essentially attempt to approximate the prior distribution function. Here a continuous smoothing technique which is based on a smooth and continuous approximation to the prior density function is presented. Results from a Monte Carlo study of the Poisson distribution are reported which show that the continuous smoothing technique has desirable small-sample properties. Some comparisons with discrete smoothing techniques are also made.

Key Words: Empirical Bayes • Smoothing techniques • Monte-Carlo comparisons • Prior density approximation • Poisson distribution • Parameter estimation


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