期刊
JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION
卷 73, 期 8, 页码 563-573出版社
TAYLOR & FRANCIS LTD
DOI: 10.1080/0094965031000136003
关键词
autoregressive models; Bayesian analysis; Gibbs sampler; predictive distribution
In this paper we consider a Bayesian analysis for an autoregressive model with random normal coefficients (RCA). For the proposed procedure we use conjugate priors for some parameters and improper vague priors for others. The inference for the parameters is made via Gibbs sampler and the convergence is assessed with multiple chains and Gelman and Rubin criterium. Forecasts are based on the predictive density of future observations. Some remarks are also made regarding order determination and stationarity. Applications to simulated and real series are given.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据