Confidence intervals for coefficients of variation in two-parameter exponential distributions

Sangnawakij, Patarawan; Niwitpong, Sa-Aat

doi:10.1080/03610918.2016.1208236

Cited by 39 publications

(23 citation statements)

References 9 publications

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“…Confidence intervals for the coefficient of variation have been established for skewed distributions. Sangnawakij & Niwitpong (2017a) presented confidence interval estimations for the coefficient of variation and the difference between coefficients of variation based on MOVER, GCI, and asymptotic confidence interval for two-parameter exponential distributions, their results indicating that GCI outperformed the other methods. Thangjai & Niwitpong (2017) proposed confidence intervals for the weighted coefficients of variation of two-parameter exponential distributions using the adjusted MOVER, GCI, and large sample methods, their result showing that GCI was the best choice.…”

Section: Introductionmentioning

confidence: 99%

“…Buntao & Niwitpong (2013) produced confidence intervals for the ratio of the coefficients of variation of delta-lognormal distributions based on the GP method and the MOVER based Wald interval; they suggested that the GP method was the most appropriate. Sangnawakij & Niwitpong (2017b) constructed new confidence intervals for functions of the difference between and the ratio of the coefficients of variation with restricted parameters in two gamma distributions; they found that the expected lengths of the proposed confidence intervals were shorter than other classical estimators.…”

Section: Introductionmentioning

confidence: 99%

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

Yosboonruang¹,

Niwitpong²,

Niwitpong³

2020

PeerJ

Self Cite

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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.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

Yosboonruang¹,

Niwitpong²,

Niwitpong³

2020

PeerJ

Self Cite

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show abstract

“…Li, Song, and Shi [13] proposed a parametric bootstrap method for constructing simultaneous confidence intervals for all pairwise differences of means from several twoparameter exponential distributions. Sangnawakij and Niwitpong [18] proposed confidence intervals for the single coefficient of variation and the difference of coefficients of variation in the two-parameter exponential distributions. Krishnamoorthy and Xia [11] considered some problems related to estimating the confidence interval of the survival probability for a two-parameter exponential distribution.…”

Section: Introductionmentioning

confidence: 99%

Exact simultaneous location-scale tests for two shifted exponential samples

Mukherjee¹,

Chong²,

Marozzi³

2020

Kybernetika

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“…Confidence intervals for the coefficient of variation have been established for skewed distributions. Sangnawakij and Niwitpong (2017a) presented confidence interval estimations for the coefficient of variation and the difference between coefficients of variation based on MOVER, GCI, and asymptotic confidence interval for two-parameter exponential distributions, their results indicating that GCI outperformed the other methods. Thangjai and Niwitpong (2017) proposed confidence intervals for the weighted coefficients of variation of two-parameter exponential distributions using the adjusted MOVER, GCI, and large sample methods, their result showing that GCI was the best choice.…”

Section: Introductionmentioning

confidence: 99%

Peer Review #2 of "The Bayesian confidence intervals for measuring the difference between dispersions of rainfall in Thailand (v0.2)"

2020

View full text Add to dashboard Cite

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, it was interested to 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 were 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.

show abstract

Confidence intervals for coefficients of variation in two-parameter exponential distributions

Cited by 39 publications

References 9 publications

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

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

Exact simultaneous location-scale tests for two shifted exponential samples

Peer Review #2 of "The Bayesian confidence intervals for measuring the difference between dispersions of rainfall in Thailand (v0.2)"

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