Confidence interval estimation for the difference of censored zero-inflated gamma distributions

This paper studies the problem of constructing confidence intervals (CIs) for the difference between coefficients of variation (CV) of two censored zero-inflated gamma distributions. Firstly, we propose a Fiducial inference based method that extends the traditional CI construction method of gamma di...

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Bibliographic Details
Published in:Scientific reports 2024-11, Vol.14 (1), p.29435-14, Article 29435
Main Authors: Guo, Hongping, Zhu, Yiran, Qian, Yuhang, Wu, Min
Format: Article
Language:English
Subjects:
704/106
704/242
Binomial distribution
Censored data
Coefficient of variation
Confidence interval
Construction methods
Detection limit
Humanities and Social Sciences
Hydrologic data
Monte Carlo simulation
multidisciplinary
Precipitation data
Science
Science (multidisciplinary)
Zero-inflated gamma distribution
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Summary:This paper studies the problem of constructing confidence intervals (CIs) for the difference between coefficients of variation (CV) of two censored zero-inflated gamma distributions. Firstly, we propose a Fiducial inference based method that extends the traditional CI construction method of gamma distribution to the scenario of zero-inflated gamma distributions with censored data. Secondly, we propose a Box-Cox transformation based method, in which not only the sample data needs to be transformed, but also the detection limit of gamma distribution with censored data accordingly. Thirdly, we investigate the Method of Variance Estimate Recovery (MOVER), to combine the previous two gamma distribution CI estimates with three binomial distribution CI estimates, and obtain six combination methods. Furthermore, we conduct Monte Carlo simulations to evaluate the performances of the proposed methods, the results indicate that all CI construction methods achieve satisfactory performances in terms of coverage probability, average length and tail error rates. Finally, we perform real data analysis using 11 years of precipitation data from Zhengzhou and Lhasa.
ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-024-79706-3