A Bayesian approach to construct confidence intervals for comparing the rainfall dispersion in Thailand

PeerJ

article

Patcharee Maneerat¹  Sa-aat Niwitpong¹  Suparat Niwitpong¹ 

[1] Department of Applied Statistics, Faculty of Applied Science, King Mongkut’s University of Technology North Bangkok

关键词: Bayesian approach;    MOVER;    Delta-lognormal distribution;    Natural rainfall;    Ratio of Variances;    Highest posterior density;   

DOI  :  10.7717/peerj.8502

学科分类：社会科学、人文和艺术（综合）

来源: Inra

【 摘 要 】

Natural disasters such as drought and flooding are the consequence of severe rainfall fluctuation, and rainfall amount data often contain both zero and positive observations, thus making them fit a delta-lognormal distribution. By way of comparison, rainfall dispersion may not be similar in enclosed regions if the topography and the drainage basin are different, so it can be evaluated by the ratio of variances. To estimate this, credible intervals using the highest posterior density based on the normal-gamma prior (HPD-NG) and the method of variance estimates recovery (MOVER) for the ratio of delta-lognormal variances are proposed. Monte Carlo simulation was used to assess the performance of the proposed methods in terms of coverage probability and relative average length. The results of the study reveal that HPD-NG performed very well and was able to meet the requirements in various situations, even with a large difference between the proportions of zeros. However, MOVER is the recommended method for equal small sample sizes. Natural rainfall datasets for the northern and northeastern regions of Thailand are used to illustrate the practical use of the proposed credible intervals.

【 授权许可】

CC BY