Generalized Complementary Baseline Classes
beta bibaseline; distribution generator; function composition; sine bibaseline.
This research aims to present two generalized complementary and bibaseline classes, referred to as the Generalized Sine Bibaseline Complementary Class and the Generalized Beta Bibaseline Complementary Class, respectively. These classes generalize and generate probability distributions through the composition of functions, enabling the identification of new probabilistic distributions, distribution classes, and families of probability distributions. Based on the proposed idea, expansions for the cumulative distribution function and the probability density function were developed. The characterization properties of the classes and their respective expansions were presented, including risk function, moments, central moments of order m, moment-generating function, characteristic function, and general coefficient. Additionally, the derivatives of the log-likelihood function and a study of the support were conducted. A theoretical application of each class was also carried out, followed by an application to simulated data, as well as a real data set, comparing the proposed model with other existing models and thereby evaluating its potential relative to the others.