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Confidence interval estimation of the common mean of several gamma populations

Gamma distributions are widely used in applied fields due to its flexibility of accommodating right-skewed data. Although inference methods for a single gamma mean have been well studied, research on the common mean of several gamma populations are sparse. This paper addresses the problem of confide...

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Autor principal: Yan, Li
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9205481/
https://www.ncbi.nlm.nih.gov/pubmed/35714130
http://dx.doi.org/10.1371/journal.pone.0269971
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author Yan, Li
author_facet Yan, Li
author_sort Yan, Li
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description Gamma distributions are widely used in applied fields due to its flexibility of accommodating right-skewed data. Although inference methods for a single gamma mean have been well studied, research on the common mean of several gamma populations are sparse. This paper addresses the problem of confidence interval estimation of the common mean of several gamma populations using the concept of generalized inference and the method of variance estimates recovery (MOVER). Simulation studies demonstrate that several proposed approaches can provide confidence intervals with satisfying coverage probabilities even at small sample sizes. The proposed methods are illustrated using two examples.
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spelling pubmed-92054812022-06-18 Confidence interval estimation of the common mean of several gamma populations Yan, Li PLoS One Research Article Gamma distributions are widely used in applied fields due to its flexibility of accommodating right-skewed data. Although inference methods for a single gamma mean have been well studied, research on the common mean of several gamma populations are sparse. This paper addresses the problem of confidence interval estimation of the common mean of several gamma populations using the concept of generalized inference and the method of variance estimates recovery (MOVER). Simulation studies demonstrate that several proposed approaches can provide confidence intervals with satisfying coverage probabilities even at small sample sizes. The proposed methods are illustrated using two examples. Public Library of Science 2022-06-17 /pmc/articles/PMC9205481/ /pubmed/35714130 http://dx.doi.org/10.1371/journal.pone.0269971 Text en © 2022 Li Yan https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Yan, Li
Confidence interval estimation of the common mean of several gamma populations
title Confidence interval estimation of the common mean of several gamma populations
title_full Confidence interval estimation of the common mean of several gamma populations
title_fullStr Confidence interval estimation of the common mean of several gamma populations
title_full_unstemmed Confidence interval estimation of the common mean of several gamma populations
title_short Confidence interval estimation of the common mean of several gamma populations
title_sort confidence interval estimation of the common mean of several gamma populations
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9205481/
https://www.ncbi.nlm.nih.gov/pubmed/35714130
http://dx.doi.org/10.1371/journal.pone.0269971
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