Bayesian inference and prediction analysis of the power law process based on a natural conjugate prior

DOI10.1080/00949655.2013.848452zbMath1457.62326OpenAlexW2028051642MaRDI QIDQ5220761

Yan-Ping Wang, Zhen-Zhou Lü

Publication date: 27 March 2020

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00949655.2013.848452

zbMATH Keywords

importance samplingBayesian inferencenatural conjugate priorpower law processprediction analysis

Mathematics Subject Classification ID

Bayesian inference (62F15) Applications of statistics in engineering and industry; control charts (62P30) Reliability and life testing (62N05)

Related Items (3)

Bayesian prior information fusion for power law process via evidence theory ⋮ Bayesian estimation versus maximum likelihood estimation in the Weibull-power law process ⋮ Unnamed Item

Cites Work

• Predictive analyses for nonhomogeneous Poisson processes with power law using Bayesian approach
• Bayesian inference for the power law process
• On estimating the current intensity of failure for the power-law process
• Bayesian Inference and Prediction Analysis of the Power Law Process Based on a Gamma Prior Distribution
• Estimating the Parameters of the Generalized Exponential Distribution in Presence of Hybrid Censoring
• Bayes inference for a non-homogeneous Poisson process with power intensity law (reliability)
• A natural conjugate prior for the non-homogeneous poisson process with a power law intensity function
• Sensitivity analysis of a reliability growth model
• A Bayes procedure for estimation of current system reliability
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