A novel compound G family with properties, copulas, modelling the asymmetric and positive-skewed engineering and medical data

Abstract

It is essential to use compound families in statistical modeling for asymmetric-positive-skewed reliability and relief in real-life data for a number of reasons, including the capacity to capture underlying patterns and characteristics in the data more accurately. The current work introduces a novel compound and continuous G family of probability distributions characterized by two parameters, denoted as the compounded two-parameters general Rayleigh geometric family of probabilistic distributions. The research involves rigorous calculations to ascertain and analyze the relevant mathematical properties of this newly proposed family. We present aging notions under the new family, providing corresponding density, hazard, and survival functions. Notably, a specific emphasis is placed on the examination of the reciprocal-Weibull baseline model, both from a mathematical and statistical perspective, in a dedicated section of the study. To generate various multivariate and bivariate type distributions, the copula method is employed. These newly derived models hold significant utility for effectively modeling the multivariate and bivariate data. The study showcases the wide applicability in different sides under real-life datasets. The presented applications serve as concrete demonstrations of the family's effectiveness and versatility in addressing real-world scenarios.