Estimation in autoregressive models with Markov regime
Statistics Theory
2016-08-16 v1 Statistics Theory
Abstract
In this paper we derive the consistency of the penalized likelihood method for the number state of the hidden Markov chain in autoregressive models with Markov regimen. Using a SAEM type algorithm to estimate the models parameters. We test the null hypothesis of hidden Markov Model against an autoregressive process with Markov regime.
Cite
@article{arxiv.math/0505081,
title = {Estimation in autoregressive models with Markov regime},
author = {Ricardo Ríos and Luis Rodríguez},
journal= {arXiv preprint arXiv:math/0505081},
year = {2016}
}
Comments
22 pages, 6 figures, 2 table