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Bayesian estimation for the mean of delta-gamma distributions with application to rainfall data in Thailand
Precipitation and flood forecasting are difficult due to rainfall variability. The mean of a delta-gamma distribution can be used to analyze rainfall data for predicting future rainfall, thereby reducing the risks of future disasters due to excessive or too little rainfall. In this study, we constru...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9123891/ https://www.ncbi.nlm.nih.gov/pubmed/35607452 http://dx.doi.org/10.7717/peerj.13465 |
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author | Kaewprasert, Theerapong Niwitpong, Sa-Aat Niwitpong, Suparat |
author_facet | Kaewprasert, Theerapong Niwitpong, Sa-Aat Niwitpong, Suparat |
author_sort | Kaewprasert, Theerapong |
collection | PubMed |
description | Precipitation and flood forecasting are difficult due to rainfall variability. The mean of a delta-gamma distribution can be used to analyze rainfall data for predicting future rainfall, thereby reducing the risks of future disasters due to excessive or too little rainfall. In this study, we construct credible and highest posterior density (HPD) intervals for the mean and the difference between the means of delta-gamma distributions by using Bayesian methods based on Jeffrey’s rule and uniform priors along with a confidence interval based on fiducial quantities. The results of a simulation study indicate that the Bayesian HPD interval based on Jeffrey’s rule prior performed well in terms of coverage probability and provided the shortest expected length. Rainfall data from Chiang Mai province, Thailand, are also used to illustrate the efficacies of the proposed methods. |
format | Online Article Text |
id | pubmed-9123891 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-91238912022-05-22 Bayesian estimation for the mean of delta-gamma distributions with application to rainfall data in Thailand Kaewprasert, Theerapong Niwitpong, Sa-Aat Niwitpong, Suparat PeerJ Statistics Precipitation and flood forecasting are difficult due to rainfall variability. The mean of a delta-gamma distribution can be used to analyze rainfall data for predicting future rainfall, thereby reducing the risks of future disasters due to excessive or too little rainfall. In this study, we construct credible and highest posterior density (HPD) intervals for the mean and the difference between the means of delta-gamma distributions by using Bayesian methods based on Jeffrey’s rule and uniform priors along with a confidence interval based on fiducial quantities. The results of a simulation study indicate that the Bayesian HPD interval based on Jeffrey’s rule prior performed well in terms of coverage probability and provided the shortest expected length. Rainfall data from Chiang Mai province, Thailand, are also used to illustrate the efficacies of the proposed methods. PeerJ Inc. 2022-05-18 /pmc/articles/PMC9123891/ /pubmed/35607452 http://dx.doi.org/10.7717/peerj.13465 Text en © 2022 Kaewprasert 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 Kaewprasert, Theerapong Niwitpong, Sa-Aat Niwitpong, Suparat Bayesian estimation for the mean of delta-gamma distributions with application to rainfall data in Thailand |
title | Bayesian estimation for the mean of delta-gamma distributions with application to rainfall data in Thailand |
title_full | Bayesian estimation for the mean of delta-gamma distributions with application to rainfall data in Thailand |
title_fullStr | Bayesian estimation for the mean of delta-gamma distributions with application to rainfall data in Thailand |
title_full_unstemmed | Bayesian estimation for the mean of delta-gamma distributions with application to rainfall data in Thailand |
title_short | Bayesian estimation for the mean of delta-gamma distributions with application to rainfall data in Thailand |
title_sort | bayesian estimation for the mean of delta-gamma distributions with application to rainfall data in thailand |
topic | Statistics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9123891/ https://www.ncbi.nlm.nih.gov/pubmed/35607452 http://dx.doi.org/10.7717/peerj.13465 |
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