Discrete Teissier distribution: properties, estimation and application

TL;DR

This paper introduces a discrete version of the Teissier distribution, explores its properties, estimates its parameters, and demonstrates its practical use through real data applications.

Contribution

It presents the first discrete analogue of the Teissier distribution, deriving its properties and applying estimation methods for practical data modeling.

Findings

Derived key distributional characteristics of the discrete Teissier distribution.

Estimated parameters effectively using maximum likelihood and method of moments.

Validated the model with two real-world data applications.

Abstract

In this article, a discrete analogue of continuous Teissier distribution is presented. Its several important distributional characteristics have been derived. The estimation of the unknown parameter has been done using the method of maximum likelihood and the method of moment. Two real data applications have been presented to show the applicability of the proposed model.