BAYESIAN-INFERENCE FOR STABLE-DISTRIBUTIONS

被引:81
作者
BUCKLE, DJ [1 ]
机构
[1] UNIV LONDON IMPERIAL COLL SCI & TECHNOL,DEPT MATH,LONDON,ENGLAND
关键词
GIBBS SAMPLING; METROPOLIS SAMPLING; REJECTION SAMPLING;
D O I
10.2307/2291072
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
Very little work on stable distribution parameter estimation and inference appears in the literature due to the nonexistence of the probability density function. This has led in particular to a dearth of Bayesian work in this area. But Bayesian computation via Markov chain Monte Carlo allows us to sample from the distribution of the parameters of the stable distributions, by exploiting a particular mathematical representation involving the stable density.
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页码:605 / 613
页数:9
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