ESTIMATION AND APPLICATION OF A NEW GENERALIZATION OF EXPONENTIAL DISTRIBUTION

In statistical literature, several lifetime distributions exist for real phenomena. And one of the methods to find new lifetime distribution by existing baseline distribution such a method is known as the transformation method. In this article, we proposed a generalization of the existing transformation by introducing the additional shape parameter. Here, we considered baseline distributions as an exponential distribution. Various statistical properties of the new lifetime distribution, such as survival function, hazard rate function, cumulative hazard rate function, moments, quantile function, and order statistics, have been discussed. Demonstrate the applicability and suitability of the proposed distribution. Here, we focus only on the estimation of the parameters likes MLE, LSE and also to check long-run behaviour of the estimators.

Publication Details

Journal
cyberleninka.ru
Published
2025-01-01
DOI
https://doi.org/10.24412/1932-2321-2025-284-282-294
Primary Topic
Statistical Distribution Estimation and Applications
Type
article
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article

ESTIMATION AND APPLICATION OF A NEW GENERALIZATION OF EXPONENTIAL DISTRIBUTION

cyberleninka.ru
Statistical Distribution Estimation and Applications
article

ESTIMATION AND APPLICATION OF A NEW GENERALIZATION OF EXPONENTIAL DISTRIBUTION

article en

Abstract

In statistical literature, several lifetime distributions exist for real phenomena. And one of the methods to find new lifetime distribution by existing baseline distribution such a method is known as the transformation method. In this article, we proposed a generalization of the existing transformation by introducing the additional shape parameter. Here, we considered baseline distributions as an exponential distribution. Various statistical properties of the new lifetime distribution, such as survival function, hazard rate function, cumulative hazard rate function, moments, quantile function, and order statistics, have been discussed. Demonstrate the applicability and suitability of the proposed distribution. Here, we focus only on the estimation of the parameters likes MLE, LSE and also to check long-run behaviour of the estimators.

cyberleninka.ru
Openalex Percentile: Top 61%
Statistical Distribution Estimation and Applications
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