Parameter estimations for mixed generalized exponential distribution based on progressive type-I interval censoring

Parameter estimations for mixed generalized exponential distribution based on progressive type-I interval censoring

This paper considers the estimation of parameters based on a progressively type-I interval-censored data from a mixed generalized exponential distribution. The maximum likelihood estimation is used but an analytic form cannot be obtained. The EM algorithm is applied to obtain the maximum likelihood...

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Bibliographic Details
Main Authors: Chunjie Wang, Shuying Wang, Dehui Wang, Chunjing Li, Xiaogang Dong
Format: Article
Language:English
Published: Taylor & Francis Group 2017-01-01
Series:Cogent Mathematics
Subjects:
progressive type-I interval censoring
mixed generalized exponential distribution
maximum likelihood estimation
EM algorithm
Online Access:http://dx.doi.org/10.1080/23311835.2017.1280913
Description
Summary:This paper considers the estimation of parameters based on a progressively type-I interval-censored data from a mixed generalized exponential distribution. The maximum likelihood estimation is used but an analytic form cannot be obtained. The EM algorithm is applied to obtain the maximum likelihood estimates. The performance of the estimates is judged by a simulating study and a real data is presented to illustrate the method of estimation developed here.
ISSN:2331-1835

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