基于分组数据的分位数不平等曲线与测度的估计
Estimation of quantile inequality curves and measures based on grouped data
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中文总结 AI 辅助
该研究针对分组数据，采用最小散度法估计分位数不平等曲线与测度，证明了估计量的一致性和渐近正态性，经模拟验证并通过真实数据应用说明方法有效性。
中文摘要 AI 辅助
本文考虑基于分组数据的参数模型中分位数不平等曲线与测度的估计问题，采用最小散度法估计分布的未知参数，使用多种φ-散度。证明了不平等曲线与测度的插件估计量的一致性，以及指数估计量的渐近正态性。通过模拟研究验证并比较了各方法的估计精度，还通过分析两个真实数据集说明了所提方法的实际应用。
英文摘要
Estimation of quantile inequality curves and measures is considered in a parametric model based on grouped data. The unknown parameters of the distribution are estimated using the minimum divergence method, using various $ϕ$-divergences. The consistency of the plug-in estimators of the inequality curves and measures and the asymptotic normality of the indices estimators are proved. In a simulation study, the methods are verified and compared in terms of the accuracy of the estimation. The practical applications of the proposed methods are illustrated by the analysis of two real data sets.
