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January, 1977 Prediction Sufficiency When the Loss Function Does Not Depend on The Unknown Parameter
Erik N. Torgersen
Ann. Statist. 5(1): 155-163 (January, 1977). DOI: 10.1214/aos/1176343748

Abstract

It is shown by Takeuchi and Akahira, 1974, that conditional independence together with a condition of "partial sufficiency" imply "prediction sufficiency" for loss functions not depending on the unknown parameter. We shall here prove that these conditions are necessary as well and thereby obtain a complete description, in terms of conditional expectations, of "prediction sufficiency" for loss functions not depending on the unknown parameter. It turns out that these conditions may be replaced by a condition of conditional independence for prior distributions.

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Erik N. Torgersen. "Prediction Sufficiency When the Loss Function Does Not Depend on The Unknown Parameter." Ann. Statist. 5 (1) 155 - 163, January, 1977. https://doi.org/10.1214/aos/1176343748

Information

Published: January, 1977
First available in Project Euclid: 12 April 2007

zbMATH: 0363.62006
MathSciNet: MR448644
Digital Object Identifier: 10.1214/aos/1176343748

Subjects:
Primary: 62B05
Secondary: 62C07

Keywords: conditional independence for prior distributions , minimal sufficiency , Prediction sufficiency

Rights: Copyright © 1977 Institute of Mathematical Statistics

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Vol.5 • No. 1 • January, 1977
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