Volume 19, 2015
|Page(s)||268 - 292|
|Published online||06 October 2015|
Consistency of the maximum likelihood estimate for non-homogeneous Markov–switching models
1 Universitéde Brest, UMR 6205, 29019 Brest, France
2 Université de Brest and IUF, UMR 6205, 29019 Brest, France
Revised: 12 September 2014
We prove the consistency of the maximum likelihood estimator for a large family of models generalizing the well known Markov-switching AutoRegressive (MS-AR) models by letting the transition probabilities vary in time and depend on covariates. We illustrate our theoretical result on the famous MacKenzie River lynx dataset and on a multi-site model for downscaling rainfall.
Mathematics Subject Classification: 62F12 / 62M05
Key words: Markov-switching autoregressive process / non-homogeneous hidden Markov process / maximum likelihood / consistency / stability / lynx data
© EDP Sciences, SMAI 2015
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