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2012•Journal of Henan Normal UniversityRequires access

EM Algorithm of Estimation of Parameter in Two-Parameter Exponential Model under Type-I Censoring Sample

Jixia Wang

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Abstract

In product life experimentation under Type-Ⅰ Censoring,the information between the last failure time and Type-I Censoring time was usually ignored.The paper dealt with this condition by EM algorithm.We got the iterative solution of the measure parameter of Two-Parameter Exponential Distribution.Moreover,a comparison of EM algorithm and traditional maximum likelihood estimation was made.It was a clear result that the EM algorithm was superior to traditional maximum likelihood estimation.

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What this paper is about

In product life experimentation under Type-Ⅰ Censoring,the information between the last failure time and Type-I Censoring time was usually ignored.The paper dealt with this condition by EM algorithm.We got the iterative solution of the measure parameter of Two-Parameter Exponential Distribution.Moreover,a comparison of EM algorithm and traditional maximum likelihood estimation was made.It was a clear result that the EM algorithm was superior to traditional maximum likelihood estimation.

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Available abstract

In product life experimentation under Type-Ⅰ Censoring,the information between the last failure time and Type-I Censoring time was usually ignored.The paper dealt with this condition by EM algorithm.We got the iterative solution of the measure parameter of Two-Parameter Exponential Distribution.Moreover,a comparison of EM algorithm and traditional maximum likelihood estimation was made.It was a clear result that the EM algorithm was superior to traditional maximum likelihood estimation.

Key concepts: Censoring (clinical trials), Exponential distribution, Maximum likelihood, Mathematics, Expectation–maximization algorithm, Exponential function, Estimation theory, Statistics

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