Ergodicity of autoregressive processes with Markov-switching and consistency of the maximum-likelihood estimator

被引：26

作者：

Francq, C

Roussignol, M

机构：

[1] Univ Lille 1, UFR Math, Lab Probabil & Stat, F-59655 Villeneuve Dascq, France

[2] Univ Marne Vallee, Equipe Anal & Math Appl, F-93166 Noisy Le Grand, France

来源：

STATISTICS | 1998年 / 32卷 / 02期

关键词：

non linear time series models; hidden Markov chain; switching models; maximum likelihood; consistency;

D O I：

10.1080/02331889808802659

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：

An autoregressive model with Markov-switching assumes a sequence of random vectors to be a non linear autoregressive model given a sequence of non observed state variables which forms a Markov chain. A particular case of this model is the hidden Markov model. In this paper conditions for the existence of an ergodic stationary solution are given and consistency of the maximum likelihood estimator is proved.

引用

页码：151 / 173

页数：23

共 13 条

[1]

[Anonymous], 1981, Springer Series in Statistics

[2] STATISTICAL INFERENCE FOR PROBABILISTIC FUNCTIONS OF FINITE STATE MARKOV CHAINS [J].