Journal of Statistics Applications & Probability
Abstract
In this paper, the point at issue is to deliberate point and interval estimations for the parameters of Weibull-Gamma distribution (WGD) using progressively Type-II censored (PROG-II-C) sample under step stress partially accelerated life test (SSPALT) model. The maximum likelihood (ML), Bayes, and four parametric bootstrap methods are used to obtain the point estimations for the distribution parameters and the acceleration factor. Furthermore, the approximate confidence intervals (ACIs), four bootstrap confidence intervals and credible intervals of the estimators have been gotten. The results of Bayes estimators are computed under the squared error loss (SEL) function using Markov Chain Monte Carlo (MCMC) method. Gibbs within the Metropolis–Hasting algorithm is applied to generate MCMC samples from the posterior density functions. Simulation results are carried out to explicate the precision of the estimators for the aforementioned parameters.
Digital Object Identifier (DOI)
http://dx.doi.org/10.18576/jsap/090109
Recommended Citation
M. EL-Sagheer, Rashad; A. W. Mahmoud, Mohamed; and M. M. Mansour, Mahmoud
(2020)
"Inferences for Weibull-Gamma Distribution in Presence of Partially Accelerated Life Test,"
Journal of Statistics Applications & Probability: Vol. 9:
Iss.
1, Article 9.
DOI: http://dx.doi.org/10.18576/jsap/090109
Available at:
https://digitalcommons.aaru.edu.jo/jsap/vol9/iss1/9