A comprehensive study of the extended JCA distribution with properties and applications

Muzna Sarwar; Farrukh Jamal; Zawar Hussain; Shoaib Iqbal; Rimsha Aslam

doi:10.64060/jasr.v1.i1.5

Authors

Muzna Sarwar Department of Statistics, Faculty of computing, The Islamia University of Bahawalpur, Pakistan Author
Farrukh Jamal Department of Statistics, Faculty of computing, The Islamia University of Bahawalpur, Pakistan Author
Zawar Hussain Department of Statistics, Faculty of computing, The Islamia University of Bahawalpur, Pakistan Author https://orcid.org/0000-0002-5109-3652
Shoaib Iqbal Department of Statistics, Faculty of computing, The Islamia University of Bahawalpur, Pakistan Author https://orcid.org/0009-0002-2818-8220
Rimsha Aslam Department of Statistics, Faculty of computing, The Islamia University of Bahawalpur, Pakistan Author

DOI:

https://doi.org/10.64060/jasr.v1.i1.5

Keywords:

JCA distribution, Mixture distribution, Maximum Likelihood Method

Abstract

The JCA distribution, which was first proposed by Jamal et al. (2021), was expanded in this paper. The new model is called the extended JCA distribution, or EJCA. For the researchers, this will be more adaptable and appealing. Explicit expressions for the moment generating function, the analytical form of the density and hazard, order statistics, and mode are among the mathematical properties that are derived. The maximum likelihood approach is used to estimate the model parameters. To evaluate the effectiveness of the estimation, a simulation study with a range of sample sizes is conducted. Two applications to the real-world data set demonstrate the proposed family's adaptability. We combined the classical exponential distribution with the JCA distribution. The new model is extremely flexible and combines the features of both models, including exponential with some probabilities and JCA. For the new distribution, we derive several mathematical properties and applications to actual data sets.