Discrete Kumaraswamy Erlang-Truncated Exponential Distribution with Applications to Count Data

Authors

Hussein Eledum, Department of Statistics, Faculty of Science, University of Tabuk, Tabuk, KSAFollow
Alaa R. El-Alosey, Department of Mathematics, Faculty of Science, Tanta University, Tanta, EgyptFollow

Author Country (or Countries)

KSA

Abstract

This paper defines the discrete Kumaraswamy Erlang-truncated exponential distribution (DKw ETE) using the general approach of discretizing a continuous distribution while retaining its survival function. The statistical properties of the DKw ETE distribution, such as the quantile function, moments, moment generating function, Re ́nyi entropy, and order statistics, are studied. The maximum likelihood (ML) method is utilized to estimate the model’s parameters. In contrast, the stress-strength parameter is derived and estimated using the ML method. Finally, the proposed distribution’s importance is explained by application to a real data set.

Digital Object Identifier (DOI)

http://dx.doi.org/10.18576/jsap/120232

Recommended Citation

Eledum, Hussein and R. El-Alosey, Alaa (2023) "Discrete Kumaraswamy Erlang-Truncated Exponential Distribution with Applications to Count Data," Journal of Statistics Applications & Probability: Vol. 12: Iss. 2, Article 33.
DOI: http://dx.doi.org/10.18576/jsap/120232
Available at: https://digitalcommons.aaru.edu.jo/jsap/vol12/iss2/33