Reliability analysis of K-out-of-N system for Weibull components based on generalized progressive hybrid censored data

07/26/2022
by   Subhankar Dutta, et al.
0

In this paper, we have investigated the reliability of a K-out-of-N system for the components following Weibull distribution based on the generalized progressive hybrid censored data. We have obtained the maximum likelihood estimates (MLEs) of the unknown parameters and the reliability function of the system. Using asymptotic normality property of MLEs, the corresponding asymptotic confidence intervals are constructed. Furthermore, Bayes estimates are derived under squared error loss function with informative prior by using Markov Chain Monte Carlo (MCMC) technique. Highest posterior density (HPD) credible intervals are obtained. A Monte Carlo simulation study is carried out to compare performance of the established estimates. Finally, a real data set is considered for illustrative purposes.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
03/15/2021

Estimation of parameters of the Gumbel type-II distribution under AT-II PHCS with an application of Covid-19 data

In this paper, we investigate the classical and Bayesian estimation of u...
research
12/11/2020

On the UMVUE and Closed-Form Bayes Estimator for Pr(X<Y<Z) and its Generalizations

This article considers the parametric estimation of Pr(X<Y<Z) and its ge...
research
03/30/2021

Analysis of the improved adaptive type-II progressive censoring based on competing risk data

In this paper, a competing risk model is analyzed based on the improved ...
research
04/19/2023

Statistical inference for dependent competing risks data under adaptive Type-II progressive hybrid censoring

In this article, we consider statistical inference based on dependent co...
research
06/28/2021

Parametric Analysis of Gumbel Type-II Distribution under Step-stress Life Test

In this paper, we focus on the parametric inference based on the Tampere...
research
04/21/2023

A novel distribution with upside down bathtub shape hazard rate: properties, estimation and applications

In this communication, we introduce a new statistical model and study it...
research
07/05/2018

An MCMC Approach to Empirical Bayes Inference and Bayesian Sensitivity Analysis via Empirical Processes

Consider a Bayesian situation in which we observe Y ∼ p_θ, where θ∈Θ, an...

Please sign up or login with your details

Forgot password? Click here to reset