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<p>Recent advancements in statistical research have highlighted the growing significance of quantile-based methods for assessing the uncertainty of random variables. In contrast to conventional approaches that utilize distribution functions, quantile-based techniques offer alternative insights into uncertainty quantification. This paper introduces a quantile-based framework for analyzing the extropy of record values and investigates its main theoretical properties. A nonparametric estimator is developed and evaluated using standard lifetime distributions, including the Govindarajalu model.</p>

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Quantile-Based Cumulative Past Extropy of Record Values

  • 期刊论文

  • 发表日期：

    2026年1月6日

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  • E. I. Abdul Sathar,
  • Veena L. Vijayan

摘要

Recent advancements in statistical research have highlighted the growing significance of quantile-based methods for assessing the uncertainty of random variables. In contrast to conventional approaches that utilize distribution functions, quantile-based techniques offer alternative insights into uncertainty quantification. This paper introduces a quantile-based framework for analyzing the extropy of record values and investigates its main theoretical properties. A nonparametric estimator is developed and evaluated using standard lifetime distributions, including the Govindarajalu model.