Bayesian inference for step-stress partially accelerated competing failure model under type II progressive censoring
type: Item
instance of: scholarly article
title: Bayesian inference for step-stress partially accelerated competing failure model under type II progressive censoring
zbMATH Open document ID: 1400.62228
DOI: 10.1155/2016/2097581
author: Xiaolin Shi
author: Fen Liu
author: Yimin Shi
published in: Mathematical Problems in Engineering
publication date: 2018-10-12T00:00:00Z
review text: Summary: This paper deals with the Bayesian inference on step-stress partially accelerated life tests using Type II progressive censored data in the presence of competing failure causes. Suppose that the occurrence time of the failure cause follows Pareto distribution under use stress levels. Based on the tampered failure rate model, the objective Bayesian estimates, Bayesian estimates, and E-Bayesian estimates of the unknown parameters and acceleration factor are obtained under the squared loss function. To evaluate the performance of the obtained estimates, the average relative errors (AREs) and mean squared errors (MSEs) are calculated. In addition, the comparisons of the three estimates of unknown parameters and acceleration factor for different sample sizes and different progressive censoring schemes are conducted through Monte Carlo simulations.
Mathematics Subject Classification ID: 62N05
Mathematics Subject Classification ID: 62F15
Mathematics Subject Classification ID: 62N03
Mathematics Subject Classification ID: 65C05
zbMATH DE Number: 6952886
Wikidata QID: Q59131096
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2016/2097581
OpenAlex ID: W2566066909
cites work: Objective Bayesian analysis of accelerated competing failure models under type-I censoring
cites work: Inference for accelerated competing failure models from Weibull distribution under type-I progressive hybrid censoring
cites work: Exact inference for a simple step-stress model with competing risks for failure from exponential distribution under type-II censoring
cites work: Inference for a simple step-stress model with competing risks for failure from the exponential distribution under time constraint
cites work: Estimation in step-stress partially accelerated life tests for the Burr type XII distribution using type I censoring
cites work: Bayes estimation of Gompertz distribution parameters and acceleration factor under partially accelerated life tests with type-I censoring
cites work: Estimating the parameters of Weibull distribution and the acceleration factor from hybrid partially accelerated life test
cites work: Estimating the Pareto parameters under progressive censoring data for constant-partially accelerated life tests
cites work: Q3551261
cites work: Objective Bayesian analysis for bivariate Marshall-Olkin exponential distribution
cites work: E-Bayesian estimation of failure probability and its application
cites work: E-Bayesian Estimation and Hierarchical Bayesian Estimation of Failure Probability
cites work: Q4315010
cites work: Estimations for Pareto Model Using General Progressive Censored Data and Asymmetric Loss
cites work: The generalized Pareto law as a model for progressively censored survival data
cites work: The Pareto Distribution as a Queue Service Discipline
cites work: A new Pareto-type distribution with applications in reliability and income data
cites work: Bayesian analysis for the two-parameter Pareto distribution based on record values and times
cites work: Statistical decision theory and Bayesian analysis. 2nd ed
cites work: Weibull Models
description: scientific article; zbMATH DE number 6952886