A General Class of New Continuous Mixture Distribution and Application

TL;DR

This paper introduces a new flexible continuous mixture distribution, reviews existing generalizations, and demonstrates its applicability using real data to enhance modeling capabilities.

Contribution

It proposes a novel generalized distribution with a mixing parameter and reviews recent trends in distribution generalizations.

Findings

The new distribution fits real data well.

Review of existing distribution generalizations.

Discussion of recent trends in distribution modeling.

Abstract

A generalization of a distribution increases the flexibility particularly in studying of a phenomenon and its properties. Many generalizations of continuous univariate distributions are available in literature. In this study, an investigation is conducted on a distribution and its generalization. Several available generalizations of the distribution are reviewed and recent trends in the construction of generalized classes with a generalized mixing parameter are discussed. To check the suitability and comparability, real data set have been used.