发表机构
University of Kashan（卡尚大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文提出基于varextropy的方差型不准确度量及其动态残差版本，建立理论性质与界，并开发非参数估计用于分布拟合评估与模型选择。
AI 中文摘要
本文基于varextropy概念，引入了一种基于方差的次序统计量不准确度量。所提出的度量提供了一个框架，用于量化次序统计量与其母体分布之间不准确函数的变异性。我们建立了该度量在严格递增可微变换下的变换性质，并确立了该度量的理论上下界。我们进一步开发了所提不准确度量的动态残差版本，并建立了潜在分布的特征化结果。此外，我们基于extropy和varextropy推导了动态残差不准确度量的界。最后，开发了所提度量的非参数估计量，并将其应用于实际数据，以评估候选分布的拟合优度并促进模型选择。
英文摘要
In this paper, we introduce a variance-based inaccuracy measure for order statistics based on the concept of varextropy. The proposed measure provides a framework for quantifying the variability of the inaccuracy function between an order statistic and its parent distribution. We establish a transformation property of the proposed measure under strictly increasing differentiable transformations. We establish theoretical upper and lower bounds for this measure. We further develop a dynamic residual version of the proposed inaccuracy measure and establish characterization results for the underlying distribution. Furthermore, we derive bounds for the dynamic residual inaccuracy measures based on extropy and varextropy. Finally, a nonparametric estimator of the proposed measure is developed and applied to real data to assess the goodness-of-fit of candidate distributions and facilitate model selection. 1.
