The estimations for parameter of Suja distribution with application

Strong relation between reliability studies and product quality. And reliability analysis deals with failure time of units and there are many well-known lifetime distributions. In this paper, we adopt the statistical inference of one more flexible one parameter distribution called Suja lifetime dist...

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Main Authors: Hanaa Abu-Zinadah, Tamadur Alsumairi
Format: Article
Language:English
Published: Elsevier 2024-01-01
Series:Alexandria Engineering Journal
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S111001682301058X
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author Hanaa Abu-Zinadah
Tamadur Alsumairi
author_facet Hanaa Abu-Zinadah
Tamadur Alsumairi
author_sort Hanaa Abu-Zinadah
collection DOAJ
description Strong relation between reliability studies and product quality. And reliability analysis deals with failure time of units and there are many well-known lifetime distributions. In this paper, we adopt the statistical inference of one more flexible one parameter distribution called Suja lifetime distribution. We primarily take into account four methods to estimate the distributional parameter other than the maximum likelihood estimation. The approximate confidence interval and two bootstrap confidence intervals have also been determined. The point and interval estimators of the Suja’ parameter are assessed and compared throughout the Monte Carlo simulation study. Finally, the Suja distribution is used to modeled and analyzed three real data sets.
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spelling doaj.art-aac1db5268804ca292c0f190a05770462024-01-24T05:17:16ZengElsevierAlexandria Engineering Journal1110-01682024-01-0186327334The estimations for parameter of Suja distribution with applicationHanaa Abu-Zinadah0Tamadur Alsumairi1Corresponding author.; University of Jeddah, College of Science, Department of Mathematics and Statistics, Jeddah, Saudi ArabiaUniversity of Jeddah, College of Science, Department of Mathematics and Statistics, Jeddah, Saudi ArabiaStrong relation between reliability studies and product quality. And reliability analysis deals with failure time of units and there are many well-known lifetime distributions. In this paper, we adopt the statistical inference of one more flexible one parameter distribution called Suja lifetime distribution. We primarily take into account four methods to estimate the distributional parameter other than the maximum likelihood estimation. The approximate confidence interval and two bootstrap confidence intervals have also been determined. The point and interval estimators of the Suja’ parameter are assessed and compared throughout the Monte Carlo simulation study. Finally, the Suja distribution is used to modeled and analyzed three real data sets.http://www.sciencedirect.com/science/article/pii/S111001682301058XSuja distributionMaximum likelihood EstimatorsLeast squares estimatorsWeighted least squares estimatorsPercentiles estimatorsBootstrap confidence intervals
spellingShingle Hanaa Abu-Zinadah
Tamadur Alsumairi
The estimations for parameter of Suja distribution with application
Alexandria Engineering Journal
Suja distribution
Maximum likelihood Estimators
Least squares estimators
Weighted least squares estimators
Percentiles estimators
Bootstrap confidence intervals
title The estimations for parameter of Suja distribution with application
title_full The estimations for parameter of Suja distribution with application
title_fullStr The estimations for parameter of Suja distribution with application
title_full_unstemmed The estimations for parameter of Suja distribution with application
title_short The estimations for parameter of Suja distribution with application
title_sort estimations for parameter of suja distribution with application
topic Suja distribution
Maximum likelihood Estimators
Least squares estimators
Weighted least squares estimators
Percentiles estimators
Bootstrap confidence intervals
url http://www.sciencedirect.com/science/article/pii/S111001682301058X
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