Journal
MATHEMATICS
Volume 11, Issue 4, Pages -Publisher
MDPI
DOI: 10.3390/math11040927
Keywords
parameter estimation; gamma distribution; representative points; mean squared error; quantile estimator
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This paper presents new methods for parameter estimation of gamma distribution using representative points. The first part discusses the theoretical existence and uniqueness of gamma mean squared error representative points (MSE-RPs). By comparing three types of representative points, the second part demonstrates that gamma MSE-RPs perform well in parameter estimation and simulation. The last part proposes a new Harrel-Davis sample standardization technique. Simulation studies show that standardized samples can improve estimation performance or generate MSE-RPs. Additionally, a real data analysis indicates that the proposed technique efficiently estimates gamma parameters.
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.
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