A Note on the Mixture Transition Distribution and Hidden Markov Models

7 Pages Posted: 15 Feb 2010

See all articles by Francesco Bartolucci

Francesco Bartolucci

Università di Perugia - Finanza e Statistica - Dipartimento di Economia

Alessio Farcomeni

affiliation not provided to SSRN

Abstract

We discuss an interpretation of the mixture transition distribution (MTD) for discrete-valued time series which is based on a sequence of independent latent variables which are occasion-specific. We show that, by assuming that this latent process follows a first order Markov Chain, MTD can be generalized in a sensible way. A class of models results which also includes the hidden Markov model (HMM). For these models we outline an EM algorithm for the maximum likelihood estimation which exploits recursions developed within the HMM literature. As an illustration, we provide an example based on the analysis of stock market data referred to different American countries.

Suggested Citation

Bartolucci, Francesco and Farcomeni, Alessio, A Note on the Mixture Transition Distribution and Hidden Markov Models. Journal of Time Series Analysis, Vol. 31, Issue 2, pp. 132-138, March 2010, Available at SSRN: https://ssrn.com/abstract=1552222 or http://dx.doi.org/10.1111/j.1467-9892.2009.00650.x

Francesco Bartolucci (Contact Author)

Università di Perugia - Finanza e Statistica - Dipartimento di Economia ( email )

06123

Alessio Farcomeni

affiliation not provided to SSRN

No Address Available

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