Stochastic Modelling on New Mixture Distribution with Properties and Their Application

In this article, the authors propose a new two-parameter continuous distribution. It is called a new mixture distribution because it comes from the unique combination of exponential and gamma distributions (MEGD). Some statistical properties of the distribution are derived, such as the moments, moments generating function, reliability analysis. Also, the distribution of order statistics is presented, and entropies are derived. The application of the maximum likelihood estimation technique to the performance of traditional parameter estimates. Two authentic data sets describing cancer patients' survival are used to empirically demonstrate the potential importance and usability of the proposed distribution. Comparing the new mixture distribution to some other competing distribution, the analysis's results demonstrated that it performed quite well.

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Publication Details

Journal
International Journal of Mathematics Statistics and Computer Science
Published
2024-10-13
DOI
https://doi.org/10.59543/ijmscs.v2i.9015
Citations
1
Primary Topic
Bayesian Methods and Mixture Models
Type
article
Field-Weighted Citation Impact
0.35
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article

Stochastic Modelling on New Mixture Distribution with Properties and Their Application

S. Murugan, M. Sakthivel
1 citations
International Journal of Mathematics Statistics and Computer Science
Bayesian Methods and Mixture Models
0.35
article

Stochastic Modelling on New Mixture Distribution with Properties and Their Application

S. Murugan, M. Sakthivel
article en
1 citations

Abstract

In this article, the authors propose a new two-parameter continuous distribution. It is called a new mixture distribution because it comes from the unique combination of exponential and gamma distributions (MEGD). Some statistical properties of the distribution are derived, such as the moments, moments generating function, reliability analysis. Also, the distribution of order statistics is presented, and entropies are derived. The application of the maximum likelihood estimation technique to the performance of traditional parameter estimates. Two authentic data sets describing cancer patients' survival are used to empirically demonstrate the potential importance and usability of the proposed distribution. Comparing the new mixture distribution to some other competing distribution, the analysis's results demonstrated that it performed quite well.

International Journal of Mathematics Statistics and Computer ScienceVol. 1
Annamalai University (IN)
Openalex Percentile: Top 33%
Bayesian Methods and Mixture Models
0.35
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