2010•Science Technology and EngineeringRequires access

Maximum Likelihood Parameter Estimation of Exponential Distribution Based on Incomplete Sample

Xue-Fang Li

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Abstract

There are many methods to deal with measuring data in survival analysis. Maximum likelihood estimation is the most popular one. Under exponential distribution,maximum likelihood estimators of the parameter for Type-I censored data and Type-II censored data are obtained,and a general expression of maximum likelihood estimator for right randomly censoring data is also derived. Moreover,a graphical method is developed to solve maximum likelihood estimation of paremeter for Packet censored data.

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What this paper is about

There are many methods to deal with measuring data in survival analysis. Maximum likelihood estimation is the most popular one. Under exponential distribution,maximum likelihood estimators of the parameter for Type-I censored data and Type-II censored data are obtained,and a general expression of maximum likelihood estimator for right randomly censoring data is also derived. Moreover,a graphical method is developed to solve maximum likelihood estimation of paremeter for Packet censored data.

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Available abstract

There are many methods to deal with measuring data in survival analysis. Maximum likelihood estimation is the most popular one. Under exponential distribution,maximum likelihood estimators of the parameter for Type-I censored data and Type-II censored data are obtained,and a general expression of maximum likelihood estimator for right randomly censoring data is also derived. Moreover,a graphical method is developed to solve maximum likelihood estimation of paremeter for Packet censored data.

Key concepts: Censoring (clinical trials), Maximum likelihood sequence estimation, Maximum likelihood, Statistics, Mathematics, Estimator, Exponential distribution, Restricted maximum likelihood

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