Maximum likelihood estimation for multivariate observations of Markov sources

✍ Scribed by Liporace, L.

• Book ID: 114635185
• Publisher: IEEE
• Year: 1982
• Tongue: English
• Weight: 728 KB
• Volume: 28
• Category: Article
• ISSN: 0018-9448
• DOI: 10.1109/tit.1982.1056544

✦ Synopsis

Parameter estimation for multivariate functions of Markov chains, a class of versatile statistical models for vector random processes, is discussed. The model regards an ordered sequence of vectors as noisy multivariate observations of a Markov chain. Mixture distributions are a special case. The foundations of the theory presented here were established by Baum, Petrie, Soules, and Weiss. A powerful representation theorem by Fan is employed to generalize the analysis of Baum, et al. to a larger class of distributions.