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2010•Mathematica ApplicataRequires access

A New Algorithm for MLE of Exponentiated Weibull Distribution with Censoring Data

Zehui Li

Open publisher page 2 citations

Abstract

In this paper,we study the maximum likelihood estimation(MLE) problem for the exponentiated weibull(EW) distribution with consideration of censoring data.Since censoring data in kind of incomplete data,we propose to use EM algorithm to compute the MLEs of the parameters.The EM algorithm could be less effective.To improve effectiveness,a new algorithm is also employed.The new algorithm is discussed via simulation studies and a real life data analysis is presented to illustrate the method.

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What this paper is about

In this paper,we study the maximum likelihood estimation(MLE) problem for the exponentiated weibull(EW) distribution with consideration of censoring data.Since censoring data in kind of incomplete data,we propose to use EM algorithm to compute the MLEs of the parameters.The EM algorithm could be less effective.To improve effectiveness,a new algorithm is also employed.The new algorithm is discussed via simulation studies and a real life data analysis is presented to illustrate the method.

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OpenAlex reports 2 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

In this paper,we study the maximum likelihood estimation(MLE) problem for the exponentiated weibull(EW) distribution with consideration of censoring data.Since censoring data in kind of incomplete data,we propose to use EM algorithm to compute the MLEs of the parameters.The EM algorithm could be less effective.To improve effectiveness,a new algorithm is also employed.The new algorithm is discussed via simulation studies and a real life data analysis is presented to illustrate the method.

Key concepts: Censoring (clinical trials), Weibull distribution, Maximum likelihood, Exponentiated Weibull distribution, Statistics, Mathematics, Expectation–maximization algorithm, Algorithm

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