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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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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