Lorenz显性的似然比检验

Shen-Da Chang, P. Cheng, M. Liou
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引用次数: 0

摘要

在检验与洛伦兹优势(LD)有关的假设时,研究人员利用经验洛伦兹过程和借助自举分析的综合随机过程检验了二阶和三阶随机优势。在这些主题中,基于风险厌恶概念的三阶随机优势(TSD)分析已经使用交叉(广义)洛伦兹曲线进行了检验。这些事实促使本研究对显示无二阶(广义洛伦兹)优势的TSD的分布对进行表征。它进一步推动了似然比(LR)拟合优度检验的发展,用于通过近似卡方分布检验LD、交叉(广义)洛伦兹曲线和TSD的各自假设。使用模拟分布对拟议的LR测试进行了评估,并应用于检查世界卫生组织在2020年3月至2021年2月期间收集的双变量样本的COVID-19区域死亡计数。
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Likelihood Ratio Tests for Lorenz Dominance
In testing hypotheses pertaining to Lorenz dominance (LD), researchers have examined second- and third-order stochastic dominance using empirical Lorenz processes and integrated stochastic processes with the aid of bootstrap analysis. Among these topics, analysis of third-order stochastic dominance (TSD) based on the notion of risk aversion has been examined using crossing (generalized) Lorenz curves. These facts motivated the present study to characterize distribution pairs displaying the TSD without second-order (generalized Lorenz) dominance. It further motivated the development of likelihood ratio (LR) goodness-of-fit tests for examining the respective hypotheses of the LD, crossing (generalized) Lorenz curves, and TSD through approximate Chi-squared distributions. The proposed LR tests were assessed using simulated distributions, and applied to examine the COVID-19 regional death counts of bivariate samples collected by the World Health Organization between March 2020 and February 2021.
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