A SIMPLE ALGORITHM FOR DELTA METHOD VARIANCES FOR MULTINOMIAL POSTERIOR BAYES PROBABILITY ESTIMATES
A SIMPLE ALGORITHM FOR DELTA METHOD VARIANCES FOR MULTINOMIAL POSTERIOR BAYES PROBABILITY ESTIMATES
复制标题
DOI：
10.1080/03610919008812891
复制
发表时间：
1990-01-01
影响因子：
0.9
通讯作者：
LENGERICH, RL
中科院分区：
文献类型：
--
作者：
MENESES, J;BARTHOLOMEW, MJ;LENGERICH, RL
研究了使用从有限数据库估计的条件概率应用贝叶斯规则所导致的估计后多项概率的不确定性。开发了估计后验概率方差的一阶泰勒级数估计器。进行了模拟研究以确定这些近似方差估计的准确性。此外，还针对各种大小的数据库评估后验概率估计和方差估计的准确性。该方法适用于应用贝叶斯方法的任何常见医学诊断问题
The uncertainty in the estimated posterior multinomial probabilities which results from applying Bayes rule using conditional probabilities estimated from a limited data base is investigated. The first order Taylor series estimator for the variance of the estimated posterior probabilities was developed. A simulation study was conducted to ascertain the accuracy of these approximate variance estimates. In addition, the accuracy of both posterior probability estimates and the variance estimates is evaluated for data bases of various sizes. The method is appropriate for any of the usual medical diagnostic problems in which Bayesian methods are applied