Full Bayesian Analysis for a Class of Jump-Diffusion Models

被引：9

作者：

Rifo, Laura L. R. ^{[1
]}

Torres, Soledad ^{[2
]}

机构：

[1] Univ Estadual Campinas, Inst Math, BR-13083970 Campinas, SP, Brazil

[2] Univ Valparaiso, CIMFAV DEUV, Valparaiso, Chile

来源：

COMMUNICATIONS IN STATISTICS-THEORY AND METHODS | 2009年 / 38卷 / 08期

关键词：

Full Bayesian significance test; Jump-diffusion process;

D O I：

10.1080/03610920802395694

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 Full Bayesian Significance Test (FBST) is adjusted for jump detection in a diffusion process. Under a natural parameterization, pure diffusion can be seen as a precise hypothesis. The evidence measure defined by FBST deals with absolutely continuous posterior distributions, when posterior rates for precise hypotheses are not appropriate. Applications to simulated and real data are shown.

引用

页码：1262 / 1271

页数：10

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