Strong consistency of kernel density estimates for Markov chains failure rates

DOI10.1007/s11203-006-9003-7zbMath1284.62247OpenAlexW2084500377MaRDI QIDQ946282

C. R. Gonçalves, Gregorio S. Atuncar, Chang Chung Yu Dorea

Publication date: 22 September 2008

Published in: Statistical Inference for Stochastic Processes (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11203-006-9003-7

zbMATH Keywords

kernel density estimatorsfailure rates for Markov chain

Mathematics Subject Classification ID

Density estimation (62G07) Asymptotic properties of nonparametric inference (62G20) Markov processes: estimation; hidden Markov models (62M05) Discrete-time Markov processes on general state spaces (60J05) Reliability and life testing (62N05)

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On the asymptotic properties of some kernel estimators for continuous-time semi-Markov processes ⋮ Structural estimation of switching costs for peaking power plants ⋮ Performance evaluation and dimensioning of \(GI^X/M/c/N\) systems through kernel estimation

Cites Work

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• Strongly ergodic behavior for non-stationary Markov processes
• ASYMPTOTIC PROPERTIES FOR MAXIMUM LIKELIHOOD ESTIMATORS FOR RELIABILITY AND FAILURE RATES OF MARKOV CHAINS
• Kernel density estimation: The general case

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