Modeling Various Data Structures via the New Type II Exponentiated Half Logistic-Odd Log-Logistic-G Power Series Class of Distributions

In this paper, we introduce the type II exponentiated half logistic-odd log-logistic-G power series class of distributions for modeling symmetric, skewed and heavy-tailed data with diverse hazard rate shapes. The proposed class of distributions is obtained by compounding the generalized family of distributions involving the type II exponentiated half logistic-G and odd log-logistic-G families with a discrete power series distribution. Various statistical properties of the proposed class of distributions, including moments, survival and hazard rate functions, order statistics, probability weighted moments, and Rényi entropy are derived. The model parameters are estimated using different estimation methods, and their performance is evaluated through Monte Carlo simulation studies. Finally, the flexibility and applicability of the proposed class of distributions are illustrated using real data sets. The results demonstrate that the proposed model provides a better fit than several existing competing models.