Approximate Maximum Product Spacings Estimation for a Weibull Distribution under Progressive Censoring

It is usually recognized that the life-times of test items may not be registered exactly. Maximum product spacings (MPS) method is most suitable method, especially to those cases where one of the parameter have an unknown shifted origin. In this paper, we consider the maximum product spacings estimators (MPSE) of the shape and scale parameters and reliability function when the samples are progressive censored (PC) samples. However, maximum product spacings estimators cannot be derived in a closed form. So, we consider the approximate maximum product spacings estimators of the shape and scale parameters and reliability function when the samples are progressive censored samples. The proposed estimators are compared by performing the Monte Carlo (MC) simulation is presented. For estimating the parameters and reliability, the choice approximate maximum product spacings estimators seem to be a reasonable choice. Also, real data set based on progressive censoring scheme have been also analyzed.