In this study, estimating the difference in the percentiles of two delta-lognormal independent populations was of interest. We used several parameters in a simulation study to compare two delta-lognormal independent populations in terms of percentiles. By simulation, it was found that the coverage probabilities were sufficiently small with a small sample size (\(n = 10\), \(m = 10\) and \(n = 50\), \(m = 10\)), but when the size of the sample was large, the coverage probabilities increased in all three cases in this study. When applying our method to a real-life weather situation, we found that the rainfall data from the Ping River in Northern Thailand (Fang and Chiang Dao, Chiang Mai province) followed delta-lognormal distribution using the confidence interval of delta-lognormal distribution percentiles and that the coverage probability was well estimated.
[1]
K. Krishnamoorthy,et al.
Confidence intervals for the mean and a percentile based on zero-inflated lognormal data
,
2018
.
[2]
Romual Eloge Tchouta.
Estimating the difference of percentiles from two independent populations
,
2008
.
[3]
Confidence Intervals for Mean and Difference between Means of Normal Distributions with Unknown Coefficients of Variation
,
2017
.
[4]
K. Krishnamoorthy,et al.
Confidence limits for lognormal percentiles and for lognormal mean based on samples with multiple detection limits.
,
2011,
The Annals of occupational hygiene.
[5]
Suparat Niwitpong,et al.
Confidence Intervals for the Ratio of Means of Delta-Lognormal Distribution
,
2018,
ECONVN.
[6]
W. J. Owen,et al.
Estimation of the Mean for Lognormal Data Containing Zeroes and Left-Censored Values, with Applications to the Measure- ment of Worker Exposure to Air Contaminants
,
1980
.