Monte Carlo Methods for Bayesian Inference on the Linear Hazard Rate Distribution

DOI10.1080/03610910600716647zbMath1093.62035OpenAlexW2152094734MaRDI QIDQ5481736

Sam J. S. Wu, Chien-Tai Lin, Narayanaswamy Balakrishnan

Publication date: 10 August 2006

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

Full work available at URL: https://doi.org/10.1080/03610910600716647

zbMATH Keywords

predictiontablessimulationBayesian computationgeneral progressive type-II censoringMarkov chain Monte Carlo (MCMC) method

Mathematics Subject Classification ID

Applications of statistics to environmental and related topics (62P12) Bayesian inference (62F15) Monte Carlo methods (65C05) Numerical analysis or methods applied to Markov chains (65C40)

Related Items (8)

Planning of progressive group-censoring life tests with cost considerations ⋮ A new flexible hazard rate distribution: Application and estimation of its parameters ⋮ Change point detection in linear failure rate distribution under random censorship ⋮ The bivariate generalized linear failure rate distribution and its multivariate extension ⋮ Optimal progressive group censoring scheme under cost considerations for pareto distribution ⋮ Parameter estimates of general failure rate model: a Bayesian approach ⋮ A new generalized linear exponential distribution and its applications ⋮ Unnamed Item

Uses Software

• boa

Cites Work

• Unnamed Item
• Inference procedures for the linear failure rate model
• Order statistics from the linear-exponential distribution, part I: increasing hazard rate case
• Analysis for the Linear Failure-Rate Life-Testing Distribution
• Bayes estimation of the linear hazard-rate model
• Parameter Estimation for the Linear Hazard Rate Distribution Based on Records and Inter-record Times
• Some Analytical Properties of Bivariate Extremal Distributions
• Interval Estimation for the Two-Parameter Double Exponential Distribution

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