Risk and information in the estimation of hidden Markov models

Authors:
Vahid R. Ramezani;Steven I. Marcus;Michael Fu
Affiliations:
University of Maryland College Park, MD;University of Maryland College Park, MD;University of Maryland College Park, MD
Venue:
WSC '04 Proceedings of the 36th conference on Winter simulation
Year:
2004

Citing 2
Cited 1

An introduction to signal detection and estimation (2nd ed.)

An introduction to signal detection and estimation (2nd ed.)
Risk-sensitive filtering and smoothing for hidden Markov models

Systems & Control Letters

Asset priority risk assessment using hidden markov models

Proceedings of the 10th ACM conference on SIG-information technology education

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Abstract

In this paper, we consider the relationship between risk-sensitivity and information. Product estimators are introduced as a generalization of Maximum A Posteriori Probability (MAP) estimator for Hidden Markov Models. We study the relationship between the inclusion of higher order moments, the underlying dynamics and the availability of information. Asymptotic periodicity of these estimators and the relationship between risk and information is studied via simulation.