Estimation of Markov-modulated time-series via EM algorithm

Abstract
We consider the estimation of various Markov-modulated time series. We obtain maximum likelihood estimates of the time-series parameters including the Markov chain transition probabilities and the time-series coefficients using the expectation maximization (EM) algorithm. In addition, the recursive EM algorithm is used to obtain on-line parameter estimates. Simulation studies show that both algorithms yield satisfactory results.

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