Parameter estimation for partially observable systems subject to random failure

DOI10.1002/asmb.1920zbMath1285.62117OpenAlexW2075090660MaRDI QIDQ5414541

Michael Jong Kim, Rui Jiang, Viliam Makiš

Publication date: 6 May 2014

Published in: Applied Stochastic Models in Business and Industry (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/asmb.1920

zbMATH Keywords

EM algorithmmaximum likelihood estimationhidden Markov modelingmultivariate observationscondition-based maintenancefailing systems

Mathematics Subject Classification ID

Related Items (6)

Optimal Control of Partially Observable Semi-Markovian Failing Systems: An Analysis Using a Phase Methodology ⋮ Multi-attribute Bayesian fault prediction for hidden-state systems under condition monitoring ⋮ Bi-level Bayesian control scheme for fault detection under partial observations ⋮ Optimal Bayesian fault prediction scheme for a partially observable system subject to random failure ⋮ Model parameter estimation and residual life prediction for a partially observable failing system ⋮ Optimal Control of a Partially Observable Failing System with Costly Multivariate Observations

Cites Work

• Unnamed Item
• Unnamed Item
• Analysis of time series subject to changes in regime
• On the convergence properties of the EM algorithm
• Dynamic linear models with Markov-switching
• On recursive estimation for hidden Markov models
• Asymptotic properties of the maximum likelihood estimator in autoregressive models with Markov regime
• Parameter estimation in a condition-based maintenance model
• Economic and economic-statistical design of a chi-square chart for CBM
• Leroux's method for general hidden Markov models
• Optimal repair/replacement policy for a general repair model
• Optimal Preventive Replacement Under Minimal Repair and Random Repair Cost
• Economic and economic-statistical design of a multivariate Bayesian control chart for condition-based maintenance
• Optimal Stopping by Means of Point Process Observations with Applications in Reliability
• The EM Algorithm and Extensions, 2E
• Maximum likelihood estimation for multivariate observations of Markov sources
• A class of invariant consistent tests for multivariate normality
• Recursive filters for a partially observable system subject to random failure
• Repairable models with operating and repair times governed by phase type distributions
• Recursive algorithms for estimation of hidden Markov models and autoregressive models with Markov regime
• An EM Algorithm for Ion-Channel Current Estimation
• An inspection–repair–replacement model for a deteriorating system with unobservable state
• Imperfect repair models with preventive maintenance
• Residual Analysis for Spatial Point Processes (with Discussion)
• Optimal Replacement Under Partial Observations

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