Parametric inference of Akash distribution for Type-Ⅱ censoring with analyzing of relief times of patients

In this paper, the problem of estimating the parameter of Akash distribution applied when the lifetime of the product follow Type-Ⅱ censoring. The maximum likelihood estimators (MLE) are studied for estimating the unknown parameter and reliability characteristics. Approximate confidence interval for...

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Main Author: Tahani A. Abushal
Format: Article
Language:English
Published: AIMS Press 2021-07-01
Series:AIMS Mathematics
Subjects:
Online Access:https://www.aimspress.com/article/doi/10.3934/math.2021627?viewType=HTML
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author Tahani A. Abushal
author_facet Tahani A. Abushal
author_sort Tahani A. Abushal
collection DOAJ
description In this paper, the problem of estimating the parameter of Akash distribution applied when the lifetime of the product follow Type-Ⅱ censoring. The maximum likelihood estimators (MLE) are studied for estimating the unknown parameter and reliability characteristics. Approximate confidence interval for the parameter is derived under the s-normal approach to the asymptotic distribution of MLE. The Bayesian inference procedures have been developed under the usual error loss function through Lindley's technique and Metropolis-Hastings algorithm. The highest posterior density interval is developed by using Metropolis-Hastings algorithm. Finally, the performances of the different methods have been compared through a Monte Carlo simulation study. The application to set of real data is also analyzed using proposed methods.
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spelling doaj.art-3b7d8778dde64d5d992a44ae03cb524b2022-12-21T23:32:14ZengAIMS PressAIMS Mathematics2473-69882021-07-01610107891080110.3934/math.2021627Parametric inference of Akash distribution for Type-Ⅱ censoring with analyzing of relief times of patientsTahani A. Abushal0Department of Mathematical Sinces, Umm AL-Qura University, Makkah Al Mukarramah, 715, Saudi ArabiaIn this paper, the problem of estimating the parameter of Akash distribution applied when the lifetime of the product follow Type-Ⅱ censoring. The maximum likelihood estimators (MLE) are studied for estimating the unknown parameter and reliability characteristics. Approximate confidence interval for the parameter is derived under the s-normal approach to the asymptotic distribution of MLE. The Bayesian inference procedures have been developed under the usual error loss function through Lindley's technique and Metropolis-Hastings algorithm. The highest posterior density interval is developed by using Metropolis-Hastings algorithm. Finally, the performances of the different methods have been compared through a Monte Carlo simulation study. The application to set of real data is also analyzed using proposed methods.https://www.aimspress.com/article/doi/10.3934/math.2021627?viewType=HTMLakash distributionbayes estimatorsmlesmetropolis-hastings algorithmtype-ⅱ censoring
spellingShingle Tahani A. Abushal
Parametric inference of Akash distribution for Type-Ⅱ censoring with analyzing of relief times of patients
AIMS Mathematics
akash distribution
bayes estimators
mles
metropolis-hastings algorithm
type-ⅱ censoring
title Parametric inference of Akash distribution for Type-Ⅱ censoring with analyzing of relief times of patients
title_full Parametric inference of Akash distribution for Type-Ⅱ censoring with analyzing of relief times of patients
title_fullStr Parametric inference of Akash distribution for Type-Ⅱ censoring with analyzing of relief times of patients
title_full_unstemmed Parametric inference of Akash distribution for Type-Ⅱ censoring with analyzing of relief times of patients
title_short Parametric inference of Akash distribution for Type-Ⅱ censoring with analyzing of relief times of patients
title_sort parametric inference of akash distribution for type ii censoring with analyzing of relief times of patients
topic akash distribution
bayes estimators
mles
metropolis-hastings algorithm
type-ⅱ censoring
url https://www.aimspress.com/article/doi/10.3934/math.2021627?viewType=HTML
work_keys_str_mv AT tahaniaabushal parametricinferenceofakashdistributionfortypeiicensoringwithanalyzingofrelieftimesofpatients