Statistical analysis of Weibull distributed lifetime data under Type II progressive censoring with binomial removals

Abstract

This paper considers the analysis of Weibull distributed lifetime data observed under Type II progressive censoring with random removals, where the number of units removed at each failure time follows a binomial distribution. Maximum likelihood estimators of the parameters and their asymptotic variances are derived. The expected time required to complete the life test under this censoring scheme is investigated.

Adaptive progressive Type-II censoring

“…Moreover, this shows that these models are mixture models with mixing pmf g * m . This approach corresponds to progressive censoring models with random removals according to a probability distribution g * (see, for instance, Yuen and Tse 1996, Tse and Yuen 1998, Tse et al 2000, Tse and Xiang 2003, and Tse and Yang 2003. Such a scheme is called a simple adaptive progressive censoring scheme.…”

Design of optimal step–stress accelerated life tests under progressive type I censoring with random removals

“…Thus, the number of removals cannot be prespecified and is random pending on the outcome of the experiment. Research works on progressive censoring schemes with this random removal scheme have been reported in Elsayed and Hao (2006), Young (2000), Tse et al (2000) and Wu and Chang (2003). These works studied parameter estimation and sampling design under type II censoring with progressive random removals at normal use conditions under various lifetime distributions.…”

Estimations of the parameters of generalised exponential distribution under progressive interval type-I censoring scheme with random removals

“…It seems more logical and natural to consider these p i as random variables for the risk of dropping at the i th stage. Perhaps, keeping a similar thought in mind, Yuen and Tse (1996) and Tse, Yang, and Yuen (2000) discussed progressive censoring scheme with binomial removal. Ashour and Afify (2007) have used PITI censoring scheme with binomial removals assuming that the exact value of the lifetimes of the units are observable.…”