Applying the principle of Maximum Entropy in Bayesian Prior Distribution Assignment

被引：0

作者：

Fang Xinghua ^{[1
]}

Song Mingshun ^{[1
]}

Wang Wei ^{[2
]}

机构：

[1] China Jiliang Univ, Coll Econ & Management, Hangzhou 310018, Zhejiang, Peoples R China

[2] Binzhou Univ, Coll Econ & Management, Binzhou 256600, Peoples R China

来源：

RECENT ADVANCE IN STATISTICS APPLICATION AND RELATED AREAS, PTS 1 AND 2 | 2008年

关键词：

Bayesian Approach; Maximum Entropy; Prior Probability Distribution;

D O I：

暂无

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

Under the prior information that Upper and lower bounds of the random quantity are symmetric with respect to the best estimate, this paper analyses the Bayesian prior distribution assignment using the principle of maximum entropy (PME). With the exact lower and Upper bounds, it approves uniform for the probability density function (PDF) of the quantity and it has a Curvilinear trapezoidal form for the inexact lower and Upper bounds.

引用

页码：415 / +

页数：2