Bayesian information in an experiment and the Fisher information distance

被引：19

作者：

Walker, Stephen G. ^{[1
]}

机构：

[1] Univ Texas Austin, Dept Math, Austin, TX 78712 USA

来源：

STATISTICS & PROBABILITY LETTERS | 2016年 / 112卷

关键词：

Shannon entropy; Information; Bayesian design; DESIGNS;

D O I：

10.1016/j.spl.2016.01.014

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

There are two forms of Fisher information; for the parameter of a model and for the information in a density model. These two forms are shown to be fundamentally connected through a measure of gain in information from a Bayesian experiment. (C) 2016 Elsevier B.V. All rights reserved.

引用

页码：5 / 9

页数：5

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