CHAINING VIA ANNEALING

被引:11
作者
EVANS, M
机构
关键词
ADAPTIVE IMPORTANCE SAMPLING; CHAINING; ANNEALING; GLOBAL OPTIMIZATION; PINCUS THEOREM;
D O I
10.1214/aos/1176347989
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
Chaining, in combination with adaptive importance sampling, can provide an effective technique for the numerical evaluation of high-dimensional integrals in the context of a posterior analysis. In many statistical problems ways of applying chaining can be found which depend heavily on the structure of the problem. In this paper we consider a very general method of implementing chaining for arbitrary integrals. Also, we show that chaining can be applied to solve global optimization problems and prove several generalizations of a theorem of Pincus.
引用
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页码:382 / 393
页数:12
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