Parameter estimation for hidden Gibbs chains

The paper investigates parameter estimation for the Gibbs chain and for the partially observed Gibbs chain. A recursion technique is used for maximizing the likelihood function and for carrying out the EM algorithm when only noisy data are available. Asymptotic properties are discussed and simulation results are presented.

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Year of publication:	1990
Authors:	Qian, W. ; Titterington, D. M.
Published in:	Statistics & Probability Letters. - Elsevier, ISSN 0167-7152. - Vol. 10.1990, 1, p. 49-58
Publisher:	Elsevier
Keywords:	EM algorithm Gibbs chain Markov chain Markov random field missing data partially observed Gibbs chain

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005319534