Consistency of the maximum likelihood estimate for non-homogeneous Markov–switching models

DOI10.1051/ps/2014024zbMath1330.62101arXiv1306.2116OpenAlexW1997497569MaRDI QIDQ2786481

Pierre Ailliot, Françoise Pène

Publication date: 12 February 2016

Published in: ESAIM: Probability and Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1306.2116

zbMATH Keywords

stabilityconsistencymaximum likelihoodMarkov-switching autoregressive processnon-homogeneous hidden Markov processMacKenzie River lynx dataset

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Markov processes: estimation; hidden Markov models (62M05) Geostatistics (86A32)

Related Items

Markov-switching state-space models with applications to neuroimaging ⋮ Sparse vector Markov switching autoregressive models. Application to multivariate time series of temperature ⋮ Maximum Likelihood Estimation in Markov Regime‐Switching Models With Covariate‐Dependent Transition Probabilities ⋮ Likelihood-based analysis in mixture global vars ⋮ Estimation and asymptotics for vector autoregressive models with unit roots and Markov switching trends ⋮ Maximum likelihood estimation in hidden Markov models with inhomogeneous noise ⋮ Markov switching quantile regression models with time-varying transition probabilities

Uses Software

• NHMSAR

Cites Work

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