ON A FAMILY OF PRIOR DISTRIBUTIONS FOR A CLASS OF BAYESIAN SEARCH MODELS

被引：1

作者：

GLAZEBROOK, KD

机构：

来源：

ADVANCES IN APPLIED PROBABILITY | 1993年 / 25卷 / 03期

关键词：

BAYES SEQUENTIAL DECISION RULE; GITTINS INDEX; OPTIMAL STOPPING; SEARCH MODELS;

D O I：

10.2307/1427532

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：

We propose a two-parameter family of conjugate prior distributions for the number of undiscovered objects in a class of Bayesian search models. The family contains the one-parameter Euler and Heine families as special cases. The two parameters may be interpreted respectively as an overall success rate and a rate of depletion of the source of objects. The new family gives enhanced flexibility in modelling.

引用

页码：714 / 716

页数：3

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