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Estimation of Parameters in Weighted Generalized Beta Distributions of the Second Kind

机译:第二类加权广义Beta分布中的参数估计

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This paper applies the class of weighted generalized beta distribution of the second kind (WGB2) as descriptive models for size distribution of income. The properties of WGB2 including mean, variance, coefficient of variation (CV), coefficient of skewness (CS), coefficient of kurtosis (CK) are presented. Other properties including top-sensitive index, bottom-sensitive index, mean logarithmic deviation (MLD) index and Theil index obtained from generalized entropy (GE) are applied in this paper. WGB2 proved to be in the generalized beta-F family of distributions, and maximum likelihood estimation (MLE) is used to obtain the parameter estimates. WGB2 is fitted to U.S. family income (2001-2009) data with different values of the parameters. The empirical results show the length-biased distribution provides the best relative fit.
机译:本文将第二类加权广义β分布(WGB2)类用作收入规模分布的描述模型。介绍了WGB2的属性,包括均值,方差,变异系数(CV),偏度系数(CS),峰度系数(CK)。从广义熵(GE)获得的其他属性包括顶部敏感指数,底部敏感指数,平均对数偏差(MLD)指数和Theil指数。 WGB2被证明属于广义beta-F分布族,并且使用最大似然估计(MLE)来获取参数估计。 WGB2适合具有不同参数值的美国家庭收入(2001-2009)数据。实验结果表明,长度偏向的分布提供了最佳的相对拟合。

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