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The Bayesian confidence intervals for measuring the difference between dispersions of rainfall in Thailand
The coefficient of variation is often used to illustrate the variability of precipitation. Moreover, the difference of two independent coefficients of variation can describe the dissimilarity of rainfall from two areas or times. Several researches reported that the rainfall data has a delta-lognorma...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7415225/ https://www.ncbi.nlm.nih.gov/pubmed/32844064 http://dx.doi.org/10.7717/peerj.9662 |
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author | Yosboonruang, Noppadon Niwitpong, Sa-Aat Niwitpong, Suparat |
author_facet | Yosboonruang, Noppadon Niwitpong, Sa-Aat Niwitpong, Suparat |
author_sort | Yosboonruang, Noppadon |
collection | PubMed |
description | The coefficient of variation is often used to illustrate the variability of precipitation. Moreover, the difference of two independent coefficients of variation can describe the dissimilarity of rainfall from two areas or times. Several researches reported that the rainfall data has a delta-lognormal distribution. To estimate the dynamics of precipitation, confidence interval construction is another method of effectively statistical inference for the rainfall data. In this study, we propose confidence intervals for the difference of two independent coefficients of variation for two delta-lognormal distributions using the concept that include the fiducial generalized confidence interval, the Bayesian methods, and the standard bootstrap. The performance of the proposed methods was gauged in terms of the coverage probabilities and the expected lengths via Monte Carlo simulations. Simulation studies shown that the highest posterior density Bayesian using the Jeffreys’ Rule prior outperformed other methods in virtually cases except for the cases of large variance, for which the standard bootstrap was the best. The rainfall series from Songkhla, Thailand are used to illustrate the proposed confidence intervals. |
format | Online Article Text |
id | pubmed-7415225 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-74152252020-08-24 The Bayesian confidence intervals for measuring the difference between dispersions of rainfall in Thailand Yosboonruang, Noppadon Niwitpong, Sa-Aat Niwitpong, Suparat PeerJ Statistics The coefficient of variation is often used to illustrate the variability of precipitation. Moreover, the difference of two independent coefficients of variation can describe the dissimilarity of rainfall from two areas or times. Several researches reported that the rainfall data has a delta-lognormal distribution. To estimate the dynamics of precipitation, confidence interval construction is another method of effectively statistical inference for the rainfall data. In this study, we propose confidence intervals for the difference of two independent coefficients of variation for two delta-lognormal distributions using the concept that include the fiducial generalized confidence interval, the Bayesian methods, and the standard bootstrap. The performance of the proposed methods was gauged in terms of the coverage probabilities and the expected lengths via Monte Carlo simulations. Simulation studies shown that the highest posterior density Bayesian using the Jeffreys’ Rule prior outperformed other methods in virtually cases except for the cases of large variance, for which the standard bootstrap was the best. The rainfall series from Songkhla, Thailand are used to illustrate the proposed confidence intervals. PeerJ Inc. 2020-08-06 /pmc/articles/PMC7415225/ /pubmed/32844064 http://dx.doi.org/10.7717/peerj.9662 Text en © 2020 Yosboonruang et al. 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, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited. |
spellingShingle | Statistics Yosboonruang, Noppadon Niwitpong, Sa-Aat Niwitpong, Suparat The Bayesian confidence intervals for measuring the difference between dispersions of rainfall in Thailand |
title | The Bayesian confidence intervals for measuring the difference between dispersions of rainfall in Thailand |
title_full | The Bayesian confidence intervals for measuring the difference between dispersions of rainfall in Thailand |
title_fullStr | The Bayesian confidence intervals for measuring the difference between dispersions of rainfall in Thailand |
title_full_unstemmed | The Bayesian confidence intervals for measuring the difference between dispersions of rainfall in Thailand |
title_short | The Bayesian confidence intervals for measuring the difference between dispersions of rainfall in Thailand |
title_sort | bayesian confidence intervals for measuring the difference between dispersions of rainfall in thailand |
topic | Statistics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7415225/ https://www.ncbi.nlm.nih.gov/pubmed/32844064 http://dx.doi.org/10.7717/peerj.9662 |
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