New Approaches on Parameter Estimation of the Gamma Distribution

Author:

Ke Xiao1,Wang Sirao234ORCID,Zhou Min23,Ye Huajun23

Affiliation:

1. College of Big Data and Internet, Shenzhen Technology University, Shenzhen 518118, China

2. Faculty of Science and Technology, BNU-HKBU United International College, Zhuhai 519087, China

3. Guangdong Provincial Key Laboratory of Interdisciplinary Research and Application for Data Science, BNU-HKBU United International College, Zhuhai 519087, China

4. Department of Mathematics, Hong Kong Baptist University, Hong Kong, China

Abstract

This paper discusses new approaches to parameter estimation of gamma distribution based on representative points. In the first part, the existence and uniqueness of gamma mean squared error representative points (MSE-RPs) are discussed theoretically. In the second part, by comparing three types of representative points, we show that gamma MSE-RPs perform well in parameter estimation and simulation. The last part proposes a new Harrel–Davis sample standardization technique. Simulation studies reveal that the standardized samples can be used to improve estimation performance or generate MSE-RPs. In addition, a real data analysis illustrates that the proposed technique yields efficient estimates for gamma parameters.

Funder

Guangdong Provincial Key Laboratory of Interdisciplinary Research and Application for Data Science, BNU-HKBU United International College

Publisher

MDPI AG

Subject

General Mathematics,Engineering (miscellaneous),Computer Science (miscellaneous)

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