Recursive Parameter Estimation and Its Convergence for Multivariate Normal Hidden Markov Inhomogeneous Models
DOI:
https://doi.org/10.11113/mjfas.v19n5.3041Keywords:
Hidden Markov model inhomogeneous, Multivariat normal, Likelihood function, Expectation Maximization, Monotone convergence.Abstract
In this paper, will discussed parameter estimation and convergence analysis of multivariate normal hidden inhomogeneous Markov models. The results of this research show that by using the expectation maximization algorithm, a sequence of parameter estimators converges to a stationary point of the likelihood function in a monotonically increasing manner.
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