A nonparametric Bayesian approach to inverse problems

被引：0

作者：

Wolpert, RL ^{[1
]}

Ickstadt, K ^{[1
]}

Hansen, MB ^{[1
]}

机构：

[1] Duke Univ, Durham, NC 27706 USA

来源：

BAYESIAN STATISTICS 7 | 2003年

关键词：

gamma process; Levy process; polymer random field; reversible jump MCMC; rheology;

D O I：

暂无

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 new method for making inference about an unknown measure F(dlambda) upon observing some values of the Fredholm integral g(omega) = integral k(omega, lambda)Gamma(dlambda) of a known kernel k(omega, lambda), using Levy random fields as Bayesian prior distributions for modelling uncertainty about Gamma(dlambda). Inference is based on simulation-based MCMC methods. The method is illustrated with a problem in polymer chemistry.

引用

页码：403 / 417

页数：15

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