Estimation of lifetime distribution parameters with general progressive censoring from Imprecise data

Journal of Data Science

article

Abbas Pak¹  Mohammad Reza Mahmoudi² 

[1] Department of Computer Sciences, Faculty of Mathematical Sciences, Shahrekord University;Department of Statistics, Shiraz University

关键词: General progressive censoring;    Maximum likelihood estimation;    EM algorithm;    Missing information;   

DOI  :  10.6339/JDS.201510_13(4).0010

学科分类：土木及结构工程学

来源: JDS

【 摘 要 】

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.

【 授权许可】

CC BY