dirichlet -多项式混合分布的第三次累积量研究

Farzana Afroz
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引用次数: 0

摘要

传统上,过散参数φ是通过使用Pearson的缺乏拟合统计量x2或偏差统计量D来估计的,这在稀疏数据的情况下表现不佳。本文重点研究了一种用于稀疏多项数据的过色散参数估计器。该估计量是基于对响应变量的第3个累积量的假设而导出的。当数据来自dirichlet多项分布时,与其他三个估计器相比,已知ϕnew具有最低的均方根误差。本文导出了dirichlet -多项式有限混合分布的一阶至三阶原始矩,其数学表达式十分复杂。此外,发现该混合物的第3个累积量不满足在推导中考虑的假设,这是在新的。达卡大学学报.科学69(2):96- 100,2021 (7)
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Studying the Third Cumulant of the Mixture of Dirichlet-multinomial Distributions
Traditionally, the overdispersion parameter ϕ is estimated by using Pearson’s lack of fit statistic X2or the Deviance statistic D, which do not perform well in the case of sparse data. This paper particularly focuses on an estimator ϕnew of overdispersion parameter which was proposed for sparse multinomial data. The estimator was derived on the basis of an assumption on the 3rd cumulant of the response variable.When the data comes from the Dirichlet-multinomial distribution ϕnew is known to have the lowest root mean squared error comparing to the other three estimators. In this paper the 1st to 3rd order raw moments of the finite mixture of Dirichlet-multinomial distributions are derived, which results in complicated mathematical expressions. Furthermore, it is found that the 3rd cumulant of this mixture does not satisfy the assumption which is considered in the derivation of ϕnew . Dhaka Univ. J. Sci. 69(2): 96-100, 2021 (July)
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