| Issue |
ESAIM: PS
Volume 19, 2015
|
|
|---|---|---|
| Page(s) | 268 - 292 | |
| DOI | https://doi.org/10.1051/ps/2014024 | |
| 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
pierre.ailliot@univ-brest.fr
2 Université de Brest and IUF, UMR 6205, 29019 Brest, France
francoise.pene@univ-brest.fr
Received:
15
January
2014
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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