The Novel Odd Generalized Exponential-G Family: Statistical Properties and Applications

This article presents The Novel Odd Generalized Exponential-G family (NOGE-G), a recently discovered distribution family. The statistical properties of a new family, which includes the following, have been studied. survival function and hazard function. We considered the cumulative hazard function, its moments, the characteristic function, the quantile function, and renyi entropy. Also considered was the estimate from the Maximum Likelihood method for parameter estimation. We expanded and combined the inverse Weibull (IW) distribution with it to explore the asymptotic behaviour of the estimates under the estimating method. This resulted in a new extended distribution, which we then simulated using Monte Carlo simulations to estimate the unknown parameters The OGEIW distribution is shown to be genuinely practical and beneficial by its application to two actual data sets.

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Publication Details

Journal
Samarra Journal of Pure and Applied Science
Published
2025-06-30
DOI
https://doi.org/10.54153/sjpas.2025.v7i2.1018
Primary Topic
Diphtheria, Corynebacterium, and Tetanus
Type
article
Field-Weighted Citation Impact
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article

The Novel Odd Generalized Exponential-G Family: Statistical Properties and Applications

Samarra Journal of Pure and Applied Science
Diphtheria, Corynebacterium, and Tetanus
article

The Novel Odd Generalized Exponential-G Family: Statistical Properties and Applications

article en

Abstract

This article presents The Novel Odd Generalized Exponential-G family (NOGE-G), a recently discovered distribution family. The statistical properties of a new family, which includes the following, have been studied. survival function and hazard function. We considered the cumulative hazard function, its moments, the characteristic function, the quantile function, and renyi entropy. Also considered was the estimate from the Maximum Likelihood method for parameter estimation. We expanded and combined the inverse Weibull (IW) distribution with it to explore the asymptotic behaviour of the estimates under the estimating method. This resulted in a new extended distribution, which we then simulated using Monte Carlo simulations to estimate the unknown parameters The OGEIW distribution is shown to be genuinely practical and beneficial by its application to two actual data sets.

Samarra Journal of Pure and Applied ScienceVol. 7(2)
University of Tikrit (IQ)
Openalex Percentile: Top 35%
Diphtheria, Corynebacterium, and Tetanus
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