Estimating the average daily rainfall in Thailand using confidence intervals for the common mean of several delta-lognormal distributions

PeerJ

article

Patcharee Maneerat¹  Sa-Aat Niwitpong² 

[1] Department of Mathematics, Faculty of Science and Technology, Uttaradit Rajabhat University;Department of Applied Statistics, Faculty of Applied Science, King Mongkut’s University of Technology North Bangkok

关键词: Agriculture;    Bayesian approach;    MOVER;    Natural rainfall;    Vague prior;    Variance;   

DOI  :  10.7717/peerj.10758

学科分类：社会科学、人文和艺术（综合）

来源: Inra

【 摘 要 】

The daily average natural rainfall amounts in the five regions of Thailand can be estimated using the confidence intervals for the common mean of several delta-lognormal distributions based on the fiducial generalized confidence interval (FGCI), large sample (LS), method of variance estimates recovery (MOVER), parametric bootstrap (PB), and highest posterior density intervals based on Jeffreys’ rule (HPD-JR) and normal-gamma-beta (HPD-NGB) priors. Monte Carlo simulation was conducted to assess the performance in terms of the coverage probability and average length of the proposed methods. The numerical results indicate that MOVER and PB provided better performances than the other methods in a variety of situations, even when the sample case was large. The efficacies of the proposed methods were illustrated by applying them to real rainfall datasets from the five regions of Thailand.

【 授权许可】

CC BY