The scan sampler for time series models

被引：6

作者：

De Jong, P ^{[1
]}

机构：

[1] Univ London London Sch Econ & Polit Sci, Dept Stat, London WC2A 2AE, England

来源：

BIOMETRIKA | 1997年 / 84卷 / 04期

关键词：

exponential family; generalised linear time series; Gibbs sampling; Kalman filter; Markov chain Monte Carlo; nonparametric regression; smoothing filter; state space model; stochastic volatility; tobit models;

D O I：

10.1093/biomet/84.4.929

中图分类号：

Q [生物科学];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

An algorithm, called the scan sampler, is developed and discussed. The scan sampler has a variety of uses for time series analysis based on the state space model with non-Gaussian observations. The algorithm is based on the Kalman filter/smoothing algorithm. It can be used for Bayesian inference using Markov chain Monte Carlo and to find posterior modes.

引用

页码：929 / 937

页数：9

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