Stochastic dominance results under multivariate chain majorization for extreme order statistics of a generalized Gompertz distribution
Abstract
Abstract The generalized Gompertz distribution—an extension of the standard Gompertz distribution as well as the exponential distribution and the generalized exponential distribution—offers more flexibility in modeling survival or failure times as it introduces an additional parameter, which can account for different shapes of hazard functions. This enhances its applicability in various fields such as actuarial science, reliability engineering and survival analysis, where more complex survival models are needed to accurately capture the underlying processes. The effect of heterogeneity has generated increased interest in recent times. In this article, multivariate chain majorization methods are exploited to develop stochastic ordering results for extreme-order statistics arising from independent heterogeneous generalized Gompertz random variables with increased degree of heterogeneity.
Fields of Study & Subjects
Statistical Distribution Estimation and Applications
Financial Risk and Volatility Modeling
Hydrology and Drought Analysis
Publication details
- Journal / source
- Probability in the Engineering and Informational Sciences
- Publisher
- Cambridge University Press (CUP)
- Volume
- 40
- Issue
- 3
- Pages
- 330–354
- Publication date
- 23 January 2026
- Language
- EN