Usual stochastic orderings of the second-order statistics with dependent heterogeneous semi-parametric distribution random variables

TL;DR

This paper studies how second-order statistics from dependent, heterogeneous semi-parametric distributions compare under stochastic orders, providing theoretical conditions, numerical examples, and real data reliability analysis.

Contribution

It establishes new sufficient conditions for stochastic ordering of second-order statistics in dependent, heterogeneous semi-parametric models, extending existing theory.

Findings

Theoretical conditions for stochastic orderings are derived.

Numerical examples illustrate the theoretical results.

Real data analysis demonstrates practical applicability.

Abstract

This manuscript investigates the stochastic comparisons of the second-order statistics from dependent and heterogeneous general semi-parametric family of distributions observations. Some sufficient conditions on the usual stochastic order of the second-order statistics from dependent and heterogeneous observations are established under the p-larger order and the reciprocally majorization order. Some numerical examples are given to illustrate the theoretical findings. In addition, the results of the Theorem are applied to two important models. Finally, we use a group of real data for empirical analysis to carry out reliability analysis.