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http://dx.doi.org/10.7465/jkdi.2013.24.4.825

Estimation of confidence interval in exponential distribution for the greenhouse gas inventory uncertainty by the simulation study  

Lee, Yung-Seop (Department of Statistics, Dongguk University)
Kim, Hee-Kyung (Department of Statistics, Dongguk University)
Son, Duck Kyu (Department of Statistics, Dongguk University)
Lee, Jong-Sik (Division of Climate Change Agroecology, National Academy of Agricultural Science)
Publication Information
Journal of the Korean Data and Information Science Society / v.24, no.4, 2013 , pp. 825-833 More about this Journal
Abstract
An estimation of confidence intervals is essential to calculate uncertainty for greenhouse gases inventory. It is generally assumed that the population has a normal distribution for the confidence interval of parameters. However, in case data distribution is asymmetric, like nonnormal distribution or positively skewness distribution, the traditional estimation method of confidence intervals is not adequate. This study compares two estimation methods of confidence interval; parametric and non-parametric method for exponential distribution as an asymmetric distribution. In simulation study, coverage probability, confidence interval length, and relative bias for the evaluation of the computed confidence intervals. As a result, the chi-square method and the standardized t-bootstrap method are better methods in parametric methods and non-parametric methods respectively.
Keywords
Asymmetric distribution; bootstrap; confidence interval; exponential distribution; inventory uncertainty;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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