Recursive estimation in mixture models with Markov regime

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Sammanfattning

A recursive algorithm is proposed for estimation of parameters in mixture models, where the observations are governed by a hidden Markov chain. The performance of the algorithm is studied by simulations of a symmetric normal mixture. The algorithm seems to be stable and produce approximately normally distributed estimates, provided the adaptive matrix is kept well conditioned.
Originalspråkengelska
Sidor (från-till)1683-1690
TidskriftIEEE Transactions on Information Theory
Volym37
Nummer6
StatusPublished - 1991

Ämnesklassifikation (UKÄ)

  • Sannolikhetsteori och statistik

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