Faculty Publications

Title

Log-concavity and other concepts of bivariate increasing failure rate distributions

Document Type

Article

Keywords

Clayton's measure of association, hazard gradient, Hessian matrix, local dependence function, log-concave density, Schur-concavity

Journal/Book/Conference Title

Journal of Applied Probability

Abstract

Log-concavity of a joint survival function is proposed as a model for bivariate increasing failure rate (BIFR) distributions. Its connections with or distinctness from other notions of BIFR are discussed. A necessary and sufficient condition for a bivariate survival function to be log-concave (BIFR-LCC) is given that elucidates the impact of dependence between lifetimes on ageing. Illustrative examples are provided to explain BIFR-LCC for both positive and negative dependence.

Department

Department of Mathematics

Original Publication Date

1-1-2022

DOI of published version

10.1017/jpr.2021.54

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