A New Perspective on Cumulative Residual Rényi Entropy

Abstract

This paper introduces a new cumulative residual Rényi entropy (CRRE), which addresses limitations of the existing cumulative residual Rényi entropy. The conventional measure suffers from two primary drawbacks: its failure to converge to the cumulative residual entropy (CRE) as the order parameter approaches unity, and its lack of guaranteed positivity. Our proposed CRRE resolves these issues, offering a theoretically consistent and always nonnegative measure of uncertainty in residual lifetimes. We explore its mathematical properties, including its relationship with existing information measures. Furthermore, the concept is extended to its dynamic version, and its time-dependent characteristics are investigated. A non-parametric estimator of the proposed CRRE is developed, its almost sure convergence is established, and is validated through Monte Carlo simulation. The effectiveness of CRRE as a tool for quantifying uncertainty is confirmed through its application in chaotic theory and financial data.