The graphical method for goodness of fit test in the inverse Weibull distribution based on multiply type-II censored samples

Many studies have considered a truncated and censored samples which are type-I, type-II and hybrid censoring scheme. The inverse Weibull distribution has been utilized for the analysis of life testing and reliability data. Also, this distribution is a very flexible distribution. The inverse Rayleigh...

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Autores principales: Kang, Suk-Bok, Han, Jun-Tae
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2015
Materias:
Methodology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4676778/
https://www.ncbi.nlm.nih.gov/pubmed/26688782
http://dx.doi.org/10.1186/s40064-015-1554-x
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author Kang, Suk-Bok
Han, Jun-Tae
author_facet Kang, Suk-Bok
Han, Jun-Tae
author_sort Kang, Suk-Bok
collection PubMed
description Many studies have considered a truncated and censored samples which are type-I, type-II and hybrid censoring scheme. The inverse Weibull distribution has been utilized for the analysis of life testing and reliability data. Also, this distribution is a very flexible distribution. The inverse Rayleigh distribution and inverse exponential distribution are a special case of the inverse Weibull distribution. In this paper, we derive the approximate maximum likelihood estimators (AMLEs) of the scale parameter and the shape parameter in the inverse Weibull distribution under multiply type-II censoring. We also propose a simple graphical method for goodness-on-fit test based on multiply type-II censored samples using AMLEs.
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spelling pubmed-46767782015-12-20 The graphical method for goodness of fit test in the inverse Weibull distribution based on multiply type-II censored samples Kang, Suk-Bok Han, Jun-Tae Springerplus Methodology Many studies have considered a truncated and censored samples which are type-I, type-II and hybrid censoring scheme. The inverse Weibull distribution has been utilized for the analysis of life testing and reliability data. Also, this distribution is a very flexible distribution. The inverse Rayleigh distribution and inverse exponential distribution are a special case of the inverse Weibull distribution. In this paper, we derive the approximate maximum likelihood estimators (AMLEs) of the scale parameter and the shape parameter in the inverse Weibull distribution under multiply type-II censoring. We also propose a simple graphical method for goodness-on-fit test based on multiply type-II censored samples using AMLEs. Springer International Publishing 2015-12-12 /pmc/articles/PMC4676778/ /pubmed/26688782 http://dx.doi.org/10.1186/s40064-015-1554-x Text en © Kang and Han. 2015 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Methodology
Kang, Suk-Bok
Han, Jun-Tae
The graphical method for goodness of fit test in the inverse Weibull distribution based on multiply type-II censored samples
title The graphical method for goodness of fit test in the inverse Weibull distribution based on multiply type-II censored samples
title_full The graphical method for goodness of fit test in the inverse Weibull distribution based on multiply type-II censored samples
title_fullStr The graphical method for goodness of fit test in the inverse Weibull distribution based on multiply type-II censored samples
title_full_unstemmed The graphical method for goodness of fit test in the inverse Weibull distribution based on multiply type-II censored samples
title_short The graphical method for goodness of fit test in the inverse Weibull distribution based on multiply type-II censored samples
title_sort graphical method for goodness of fit test in the inverse weibull distribution based on multiply type-ii censored samples
topic Methodology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4676778/
https://www.ncbi.nlm.nih.gov/pubmed/26688782
http://dx.doi.org/10.1186/s40064-015-1554-x
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