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Markov Chains and Their Extensions

  • M. B. Rajarshi
Chapter
Part of the SpringerBriefs in Statistics book series (BRIEFSSTATIST)

Abstract

This chapter deals with likelihood-based inference for ergodic finite as well as infinite Markov chains. We also consider extensions of Markov chain models, such as Hidden Markov chain, Markov chains based on polytomous regression, and Raftery’s Mixture Transition Density model. These models have less number of parameters as compared to a higher order finite Markov chain. Lastly, we discuss methods of estimation in grouped data from finite Markov chains.

Keywords

Markov Chain Markov Chain Model Fisher Information Matrix Finite Markov Chain Hide Markov Chain 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© The Author(s) 2013

Authors and Affiliations

  1. 1.Department of StatisticsUniversity of PunePuneIndia

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