Recently, there is a growing interest to study the variability of uncertainty measure in information theory. For the sake of analyzing such interest, varentropy has been introduced and examined for one-sided truncated random variables. As the interval entropy measure is instrumental in summarizing various system and its components properties when it fails between two time points, exploring variability of such measure pronounces the extracted information. In this article, we introduce the concept of varentropy for doubly truncated random variable. A detailed study of theoretical results taking into account transformations, monotonicity and other conditions is proposed. A simulation study has been carried out to investigate the behavior of varentropy in shrinking interval for simulated and real-life data sets. Furthermore, applications related to the choice of most acceptable system and the first-passage times of an Ornstein–Uhlenbeck jump-diffusion process are illustrated.

最近，人们对研究信息论中不确定性测度的变异性越来越感兴趣。为了分析这种兴趣，引入了变熵并检查了单侧截断随机变量。由于区间熵度量有助于总结两个时间点之间发生故障时的各种系统及其组件的属性，因此探索此类度量的可变性可以表明提取的信息。在本文中，我们介绍了双截断随机变量的变熵的概念。提出了考虑变换、单调性和其他条件的理论结果的详细研究。我们进行了一项模拟研究，以研究模拟数据集和现实数据集收缩区间中变熵的行为。此外，