Maximum-likelihood estimation for hidden Markov models
نویسندگان
چکیده
منابع مشابه
Maximum-likelihood estimation for hidden Markov models
Hidden Markov models assume a sequence of random variables to be conditionally independent given a sequence of state variables which forms a Markov chain. Maximum-likelihood estimation for these models can be performed using the EM algorithm. In this paper the consistency of a sequence of maximum-likelihood estimators is proved. Also, the conclusion of the Shannon-McMillan-Breiman theorem on en...
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The estimation of Hidden Markov Models has attracted a lot of attention recently, see results of Legland and Mevel (2000) and Leroux (1992). The purpose of this paper is to give a view for the analysis of the maximumlikelihood estimation of HMM-s. General consistency results are compared to the new approach. The new approach is potentially useful for deriving strong approximation results, which...
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We consider the process dYt = utdt + dWt; where u is a process not necessarily adapted to FY (the ...ltration generated by the process Y ) and W is a Brownian Motion. We obtain a general representation for the likelihood ratio of the law of the Y process relative to Brownian measure. This representation involves only one basic ...lter (expectation of u conditional on observed process Y ): This ...
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ژورنال
عنوان ژورنال: Stochastic Processes and their Applications
سال: 1992
ISSN: 0304-4149
DOI: 10.1016/0304-4149(92)90141-c