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Entropy-Based Parameter Estimation for the Four-Parameter Exponential Gamma Distribution

Songbai Song, Xiaoyan Song, Yan Kang

Entropy · 2017

doi:10.3390/e19050189 (opens in a new tab)

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Abstract

Two methods based on the principle of maximum entropy (POME), the ordinary entropy method (ENT) and the parameter space expansion method (PSEM), are developed for estimating the parameters of a four-parameter exponential gamma distribution. Using six data sets for annual precipitation at the Weihe River basin in China, the PSEM was applied for estimating parameters for the four-parameter exponential gamma distribution and was compared to the methods of moments (MOM) and of maximum likelihood estimation (MLE). It is shown that PSEM enables the four-parameter exponential distribution to fit the data well, and can further improve the estimation.

Abstract licence: CC BY

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