Consistent and Asymptotically Normal Parameter Estimates for Hidden Markov Models
Ryden, Tobias
Ann. Statist., Tome 22 (1994) no. 1, p. 1884-1895 / Harvested from Project Euclid
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Hidden Markov models are today widespread for modeling of various phenomena. It has recently been shown by Leroux that the maximum-likelihood estimate (MLE) of the parameters of a such a model is consistent, and local asymptotic normality has been proved by Bickel and Ritov. In this paper we propose a new class of estimates which are consistent, asymptotically normal and almost as good as the MLE.
Publié le : 1994-12-14
Classification:  Hidden Markov model,  consistency,  asymptotic normality,  identifiability,  regenerative process,  62M09,  62F12,  62E25 
@article{1176325762,
     author = {Ryden, Tobias},
     title = {Consistent and Asymptotically Normal Parameter Estimates for Hidden Markov Models},
     journal = {Ann. Statist.},
     volume = {22},
     number = {1},
     year = {1994},
     pages = { 1884-1895},
     language = {en},
     url = {http://dml.mathdoc.fr/item/1176325762}
}

Ryden, Tobias. Consistent and Asymptotically Normal Parameter Estimates for Hidden Markov Models. Ann. Statist., Tome 22 (1994) no. 1, pp.  1884-1895. http://gdmltest.u-ga.fr/item/1176325762/