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2019•Maǧallaẗ Al-Šurūq Lil ʿulūm Al-Tiǧāriyyaẗ/Maǧallaẗ Al-Šurūq Lil ʿulūm Al-TiğāriyyaẗOpen access

Point and Interval Estimation of The Inverse Weibull Distribution Parameters under Random Censoring

Hiba Zeyada Muhammed, Essam Abd Elsalam Muhammed

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Abstract

The inverse weibull (IW) distribution has many applications in problems related to medical research and life testing. In this paper, point and interval estimation of the IW distribution parameters are considered in presence of random censoring. Maximum likelihood estimation (MLE) is considered for the models unknown parameters. Asymptotic and bootstrap confidence intervals are evaluated for the unknown parameters. Simulation study is carried out to see the performance of the maximum likelihood estimators (MLEs). One real data set has reanalyzed for illustrative purpose

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What this paper is about

The inverse weibull (IW) distribution has many applications in problems related to medical research and life testing. In this paper, point and interval estimation of the IW distribution parameters are considered in presence of random censoring. Maximum likelihood estimation (MLE) is considered for the models unknown parameters. Asymptotic and bootstrap confidence intervals are evaluated for the unknown parameters. Simulation study is carried out to see the performance of the maximum likelihood estimators (MLEs). One real data set has reanalyzed for illustrative purpose

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Available abstract

The inverse weibull (IW) distribution has many applications in problems related to medical research and life testing. In this paper, point and interval estimation of the IW distribution parameters are considered in presence of random censoring. Maximum likelihood estimation (MLE) is considered for the models unknown parameters. Asymptotic and bootstrap confidence intervals are evaluated for the unknown parameters. Simulation study is carried out to see the performance of the maximum likelihood estimators (MLEs). One real data set has reanalyzed for illustrative purpose

Key concepts: Censoring (clinical trials), Weibull distribution, Interval estimation, Statistics, Point estimation, Mathematics, Estimation, Econometrics

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