On dynamic mutual information for bivariate lifetimes

TL;DR

This paper explores dynamic mutual information in bivariate lifetimes, analyzing dependence at different ages and times, providing bounds, explicit calculations, and a copula-based framework for better understanding multicomponent system reliability.

Contribution

It introduces a novel dynamic mutual information framework for bivariate lifetimes, including bounds, explicit formulas, and a copula-based approach, advancing reliability analysis methods.

Findings

Derived bounds for dynamic mutual information.

Explicit calculation of mutual information between order statistics.

Distribution-free results for minimum and maximum lifetimes.

Abstract

We consider dynamic versions of the mutual information of lifetime distributions, with focus on past lifetimes, residual lifetimes and mixed lifetimes evaluated at different instants. This allows to study multicomponent systems, by measuring the dependence in conditional lifetimes of two components having possibly different ages. We provide some bounds, and investigate the mutual information of residual lifetimes within the time-transformed exponential model (under both the assumptions of unbounded and truncated lifetimes). Moreover, with reference to the order statistics of a random sample, we evaluate explicitly the mutual information between the minimum and the maximum, conditional on inspection at different times, and show that it is distribution-free. Finally, we develop a copula-based approach aiming to express the dynamic mutual information for past and residual bivariate lifetimes in an alternative way.