An expectation maximization algorithm to model failure times by continuous-time Markov chains

DOI10.1155/2010/242567zbMath1203.90055OpenAlexW2099434859WikidataQ58652970 ScholiaQ58652970MaRDI QIDQ1958812

Zhiping Chen, Qihong Duan, Dengfu Zhao

Publication date: 30 September 2010

Published in: Mathematical Problems in Engineering (Search for Journal in Brave)

Full work available at URL: https://eudml.org/doc/227549

zbMATH Keywords

supplementary variablesmaximum likelihood estimators

Mathematics Subject Classification ID

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Cites Work

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• Insurance claims modulated by a hidden Brownian marked point process
• Fractal time series -- A tutorial review
• Computing multiple integrals involving matrix exponentials
• How to Identify a Bathtub Hazard Rate
• New finite-dimensional filters and smoothers for noisily observed Markov chains
• The Method of Stages for Non-Markov Models
• Computing integrals involving the matrix exponential
• Calculating the Rate of Occurrence of Failures for Continuous-time Markov Chains with Application to a Two-component Parallel System
• Discrete-Time Expectation Maximization Algorithms for Markov-Modulated Poisson Processes

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