Prediction in trend-renewal processes for repairable systems

DOI10.1007/s11222-013-9393-5zbMath1325.60141OpenAlexW2092555596WikidataQ59394512 ScholiaQ59394512MaRDI QIDQ892810

Ryszard Magiera, Jürgen Franz, Alicja Jokiel-Rokita

Publication date: 12 November 2015

Published in: Statistics and Computing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11222-013-9393-5

zbMATH Keywords

prediction intervalnon-homogeneous Poisson processpower law processtrend-renewal processfuture failure time predictionWeibull power law trend-renewal process

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Point estimation (62F10) Reliability, availability, maintenance, inspection in operations research (90B25) Reliability and life testing (62N05) Prediction theory (aspects of stochastic processes) (60G25) Renewal theory (60K05)

Related Items (3)

Two-state optimal maintenance planning of repairable systems with covariate effects ⋮ Bayesian estimation versus maximum likelihood estimation in the Weibull-power law process ⋮ Estimation of the mean value function for gamma trend renewal process

Cites Work

• Estimation of parameters for trend-renewal processes
• Statistical inference and prediction for the Weibull process with incomplete observations
• Prediction and asymptotics
• Predicting a cyclic Poisson process
• On the statistical modeling and analysis of repairable systems
• Maximum likelihood and bayes prediction of current system lifetime
• Frequentist prediction intervals and predictive distributions
• Prediction Intervals for the Weibull Process
• Statistical models based on counting processes
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