Asymptotic Expansion of the Risk Difference of the Bayesian Spectral Density in the Autoregressive Moving Average Model

被引：0

作者：

Tanaka, Fuyuhiko ^{[1
]}

Komaki, Fumiyasu ^{[1
,2
]}

机构：

[1] Univ Tokyo, Dept Math Informat, Bunkyo Ward, Hongo 7-3-1, Tokyo 1138656, Japan

[2] RIKEN, Brain Sci Inst, Tokyo, Japan

来源：

SANKHYA-SERIES A-MATHEMATICAL STATISTICS AND PROBABILITY | 2011年 / 73卷 / 01期

关键词：

Autoregressive moving average model; Bayesian estimation; information geometry; noninformative prior; spectral density;

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：

The autoregressive moving average (ARMA) model is one of the most important models in time series analysis. We consider Bayesian estimation of an unknown spectral density in the ARMA model. In i.i.d. cases, it is known that Bayesian predictive densities based on a superharmonic prior asymptotically dominate those based on the Jeffreys prior. It was shown by using the asymptotic expansion of the risk difference. We obtain the corresponding results for the ARMA model.

引用

页码：162 / 184

页数：23

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