TL-Moments for Type-I Censored Data with an Application to the Weibull Distribution

This paper aims to provide an adaptation of the trimmed L (TL)-moments method to censored data. The present study concentrates on Type-I censored data. The idea of using TL-moments with censored data may seem conflicting. However, our perspective is that we can use data censored from one side and tr...

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Main Authors: Hager A. Ibrahim, Mahmoud Riad Mahmoud, Fatma A. Khalil, Ghada A. El-Kelany
Format: Article
Language:English
Published: MDPI AG 2018-09-01
Series:Mathematical and Computational Applications
Subjects:
Online Access:http://www.mdpi.com/2297-8747/23/3/47
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spelling doaj-97545bdf125e4769ab1912ec9b9f015f2020-11-24T22:23:18ZengMDPI AGMathematical and Computational Applications2297-87472018-09-012334710.3390/mca23030047mca23030047TL-Moments for Type-I Censored Data with an Application to the Weibull DistributionHager A. Ibrahim0Mahmoud Riad Mahmoud1Fatma A. Khalil2Ghada A. El-Kelany3Department of Statistics, Faculty of Commerce, Al-Azhar University (Girls’ Branch), Cairo, EgyptDepartment of Mathematical Statistics, Institute of Statistics Studies and Research, Cairo University, Giza, EgyptDepartment of Statistics, Faculty of Commerce, Al-Azhar University (Girls’ Branch), Cairo, EgyptDepartment of Statistics, Faculty of Commerce, Al-Azhar University (Girls’ Branch), Cairo, EgyptThis paper aims to provide an adaptation of the trimmed L (TL)-moments method to censored data. The present study concentrates on Type-I censored data. The idea of using TL-moments with censored data may seem conflicting. However, our perspective is that we can use data censored from one side and trimmed from the other side. This study is applied to estimate the two unknown parameters of the Weibull distribution. The suggested point is compared with direct L-moments and maximum likelihood (ML) methods. A Monte Carlo simulation study is carried out to compare these methods in terms of estimate average, root of mean square error (RMSE), and relative absolute biases (RABs).http://www.mdpi.com/2297-8747/23/3/47censored dataestimationdirect L-momentsTL-momentsmaximum likelihoodWeibull distribution
collection DOAJ
language English
format Article
sources DOAJ
author Hager A. Ibrahim
Mahmoud Riad Mahmoud
Fatma A. Khalil
Ghada A. El-Kelany
spellingShingle Hager A. Ibrahim
Mahmoud Riad Mahmoud
Fatma A. Khalil
Ghada A. El-Kelany
TL-Moments for Type-I Censored Data with an Application to the Weibull Distribution
Mathematical and Computational Applications
censored data
estimation
direct L-moments
TL-moments
maximum likelihood
Weibull distribution
author_facet Hager A. Ibrahim
Mahmoud Riad Mahmoud
Fatma A. Khalil
Ghada A. El-Kelany
author_sort Hager A. Ibrahim
title TL-Moments for Type-I Censored Data with an Application to the Weibull Distribution
title_short TL-Moments for Type-I Censored Data with an Application to the Weibull Distribution
title_full TL-Moments for Type-I Censored Data with an Application to the Weibull Distribution
title_fullStr TL-Moments for Type-I Censored Data with an Application to the Weibull Distribution
title_full_unstemmed TL-Moments for Type-I Censored Data with an Application to the Weibull Distribution
title_sort tl-moments for type-i censored data with an application to the weibull distribution
publisher MDPI AG
series Mathematical and Computational Applications
issn 2297-8747
publishDate 2018-09-01
description This paper aims to provide an adaptation of the trimmed L (TL)-moments method to censored data. The present study concentrates on Type-I censored data. The idea of using TL-moments with censored data may seem conflicting. However, our perspective is that we can use data censored from one side and trimmed from the other side. This study is applied to estimate the two unknown parameters of the Weibull distribution. The suggested point is compared with direct L-moments and maximum likelihood (ML) methods. A Monte Carlo simulation study is carried out to compare these methods in terms of estimate average, root of mean square error (RMSE), and relative absolute biases (RABs).
topic censored data
estimation
direct L-moments
TL-moments
maximum likelihood
Weibull distribution
url http://www.mdpi.com/2297-8747/23/3/47
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