Journal of Data Science

Abstact:The problem of estimating lifetime distribution parameters under general progressive censoring originated in the context of reliability. But traditionally it is assumed that the available data from this censoring scheme are performed in exact numbers. However, in many life testing and reliability studies, it is not possible to obtain the measurements of a statistical experiment exactly, but is possible to classify them into fuzzy sets. This paper deals with the estimation of lifetime distribution parameters under general progressive Type-II censoring scheme when the lifetime observations are reported by means of fuzzy numbers. A new method is proposed to determine the maximum likelihood estimates of the parameters of interest. The methodology is illustrated with two popular models in lifetime analysis, the Rayleigh and Lognormal lifetime distributions.