GIBBS SAMPLING FOR SARMA MODELS

被引：0
|
作者：
Ismail, Mohamed A. [1 ]
Amin, Ayman A. [2 ]
机构：
[1] Cairo Univ, Dept Stat, Giza, Egypt
[2] Menoufia Univ, Dept Stat, Menoufia, Egypt
来源：
PAKISTAN JOURNAL OF STATISTICS | 2014年 / 30卷 / 02期
关键词：
Seasonal ARMA Model; Normal Gamma Prior; Posterior Distribution; Gibbs Sampling; Egyptian Imports of Durable Consumption Goods; BAYESIAN-ESTIMATION; REGRESSION-MODELS; ARMA;
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：
This paper introduces a fast, easy and accurate Gibbs sampling algorithm to develop a Bayesian inference for a multiplicative seasonal autoregressive moving average (SARMA) model. The proposed algorithm generates from normal and inverse gamma distributions and does not involve any Metropolis-Hastings generation. Simulated examples and a real data set are used to illustrate the proposed algorithm.
引用
收藏
页码：153 / 168
页数：16
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