Faculty Publications
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
Recommended Citation
Gupta, Ramesh C. and Kirmani, S. N.U.A., "Log-Concavity And Other Concepts Of Bivariate Increasing Failure Rate Distributions" (2022). Faculty Publications. 5216.
https://scholarworks.uni.edu/facpub/5216
