Estimating a Markov transition matrix from observational data

Estimating a Markov transition matrix from observational data

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Article ID: iaor19952255
Country: United Kingdom
Volume: 46
Issue: 3
Start Page Number: 405
End Page Number: 410
Publication Date: Mar 1995
Journal: Journal of the Operational Research Society
Authors: , ,
Abstract:

Markov chains are frequently used in Operational Research to describe how a system changes over time, its behaviour being governed by its transition matrix. This paper describes a technique for finding a maximum likelihood estimate for such a transition matrix when a system is observed at infrequent time intervals. The technique is called the EM Algorithm which, for this kind of problem, has distinct advantages over other methods of optimization.

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