In this paper we introduce a new scheme of censoring and study it under the Weibull distribution. This scheme is a mixture of progressive Type II censoring and self relocating design which was first introduced by Srivastava [8]. We show the superiority of this censoring scheme (PSRD) relative to the classical schemes with respect to “asymptotic variance”. Comparisons are also made with respect ...

Objectives Methods accounting for competing risks in time-to-event problems are becoming common in mainstream statistical analyses. Standard approaches include those based on log-rank type tests [1] and cumulative incidence regression [2]. These approaches are based on weighting competing events by the censoring distribution. The usual cumulative incidence regression uses weights based on the p...

This paper is concerned with the estimators problems of the generalized Weibull distribution based on Type-I hybrid progressive censoring scheme (Type-I PHCS) in the presence of competing risks when the cause of failure of each item is known. Maximum likelihood estimates and the corresponding Fisher information matrix are obtained. We generalized Kundu and Joarder [7] results in the case of the...

This article presents a test based on quadratic form using Type-2 with replacement-censored sample for testing exponentiality against weibull IFR/DFR alternative. The percentile points and powers are simulated. The proposed test is compared with that of Bain and Engelhardt (1986) test. An example based on Type-2 censoring is also discussed.

This article studies the E-Bayesian estimation of unknown parameter Lomax distribution based on generalized Type-I hybrid censoring. Under square error loss and LINEX functions, we get compare its effectiveness with Bayesian estimation. To measure estimation, expectation mean (E-MSE) is introduced. With Markov chain Monte Carlo technology, estimations are computed. Metropolis–Hastings algorithm...