APPROXIMATION OF BAYESIAN POSTERIOR DENSITIES IN THE HETEROSKEDASTIC ERROR REGRESSION-MODEL

被引：0
|
作者：
BRORSEN, BW
机构：
[1] Oklahoma State University, Stillwater
来源：
ECONOMICS LETTERS | 1992年 / 38卷 / 01期
关键词：
D O I：
10.1016/0165-1765(92)90153-P
中图分类号：
F [经济];
学科分类号：
02 ;
摘要：
One reason Bayesian methods are rarely used is that they frequently require multilevel numerical integrations for marginal inference. This paper shows how to avoid the need for numerical integration in the heteroskedastic error regression model by approximating the posterior densities.
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页码：1 / 7
页数：7
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