Bayesian Inference and Prediction Analysis of the Power Law Process Based on a Gamma Prior Distribution

DOI10.1080/03610918.2011.575504zbMath1227.62016OpenAlexW1970003575MaRDI QIDQ3102887

Yan-Ping Wang, Zhen-Zhou Lü

Publication date: 25 November 2011

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918.2011.575504

zbMATH Keywords

importance samplingreliability growth

Mathematics Subject Classification ID

Related Items (5)

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 ⋮ Bayesian estimation of the expected time of first arrival past a truncated time \(T\): the case of NHPP with power law intensity ⋮ Bayesian inference and prediction analysis of the power law process based on a natural conjugate prior

Cites Work

• Unnamed Item
• 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 Computation for Nonhomogeneous Poisson Processes in Software Reliability
• 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)
• Sensitivity analysis of a reliability growth model
• Adaptive Rejection Sampling for Gibbs Sampling
• A Bayes procedure for estimation of current system reliability

This page was built for publication: Bayesian Inference and Prediction Analysis of the Power Law Process Based on a Gamma Prior Distribution