Bayesian analysis of Gumbel distributed data

被引：7
|
作者：
Chechile, RA [1 ]
机构：
[1] Tufts Univ, Dept Psychol, Medford, MA 02155 USA
来源：
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS | 2001年 / 30卷 / 03期
关键词：
extreme-order distributions; Gumbel conjugate funtion; small-sample Gumbel analysis; exact posterior parameter sampling;
D O I：
10.1081/STA-100002093
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：
The form and conditions are delineated for a Bayesian conjugate prior probability density function for Gumbel distributed data. The solution is provided for the posterior normalization constant along with the marginal distribution for the Gumbel scale-factor parameter, delta. Moreover, an exact Monte Carlo algorithm is provided to evaluate the properties of the posterior distribution for the location and scale factor parameters along with their correlation. The method for analyzing Gumbel distributed data is illustrated with several applications.
引用
收藏
页码：485 / 496
页数：12
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