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The Bayesian confidence intervals for measuring the difference between dispersions of rainfall in Thailand

Authors :
Noppadon Yosboonruang
Sa-Aat Niwitpong
Suparat Niwitpong
Source :
PeerJ, Vol 8, p e9662 (2020)
Publication Year :
2020
Publisher :
PeerJ Inc., 2020.

Abstract

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.

Details

Language :
English
ISSN :
21678359
Volume :
8
Database :
Directory of Open Access Journals
Journal :
PeerJ
Publication Type :
Academic Journal
Accession number :
edsdoj.5dfe8278a9b046918406989e46c93c70
Document Type :
article
Full Text :
https://doi.org/10.7717/peerj.9662