The Khalil New Generalized Rayleigh (KNGR) Distribution:Statistical Properties, Estimation, and Applications

This study introduces the Khalil New Generalized Rayleigh (KNG-R) distribution, a novel and flexible lifetime model derived by ‎applying the Khalil New Generalized Family (KNGF) generator to the Rayleigh distribution. The proposed model extends the Ray-‎leigh family by incorporating additional parameters that enhance its ability to capture diverse data behaviors such as increasing, ‎creasing, and bathtub-shaped hazard rates. Key statistical properties, including the probability density function, cumulative distribution function, moments, moment-generating function, entropy, and quantile function, were derived. Additionally, parameter estimation was conducted using the maximum likelihood method, and a Monte Carlo simulation confirms the consistency and efficiency of ‎the estimators. The KNG-R distribution was applied to three real datasets and outperformed competing distributions, including the ‎Weibull–Rayleigh, TIIEHL-PLo, SMR, and Rayleigh models, based on log-likelihood, AIC, BIC, and AICc criteria. The results ‎demonstrate that the KNG-R is a powerful and adaptable distribution suitable for modeling complex lifetime and reliability data.

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Publication Details

Journal
International Journal of Advanced Statistics and Probability
Published
2025-11-20
DOI
https://doi.org/10.14419/txpaq681
Primary Topic
Statistical Distribution Estimation and Applications
Type
article
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article

The Khalil New Generalized Rayleigh (KNGR) Distribution:Statistical Properties, Estimation, and Applications

Kwame Owusu Edusei, Osei Antwi, Richard Kwabena Nkrumah, Angela Nkrumah et al.
International Journal of Advanced Statistics and Probability
Statistical Distribution Estimation and Applications
article

The Khalil New Generalized Rayleigh (KNGR) Distribution:Statistical Properties, Estimation, and Applications

Kwame Owusu Edusei, Osei Antwi, Richard Kwabena Nkrumah, Angela Nkrumah, Yeboah Andrews Murphy
article en

Abstract

This study introduces the Khalil New Generalized Rayleigh (KNG-R) distribution, a novel and flexible lifetime model derived by ‎applying the Khalil New Generalized Family (KNGF) generator to the Rayleigh distribution. The proposed model extends the Ray-‎leigh family by incorporating additional parameters that enhance its ability to capture diverse data behaviors such as increasing, ‎creasing, and bathtub-shaped hazard rates. Key statistical properties, including the probability density function, cumulative distribution function, moments, moment-generating function, entropy, and quantile function, were derived. Additionally, parameter estimation was conducted using the maximum likelihood method, and a Monte Carlo simulation confirms the consistency and efficiency of ‎the estimators. The KNG-R distribution was applied to three real datasets and outperformed competing distributions, including the ‎Weibull–Rayleigh, TIIEHL-PLo, SMR, and Rayleigh models, based on log-likelihood, AIC, BIC, and AICc criteria. The results ‎demonstrate that the KNG-R is a powerful and adaptable distribution suitable for modeling complex lifetime and reliability data.

International Journal of Advanced Statistics and ProbabilityVol. 12(2)
Accra Technical University (GH), Ghana Health Service (GH)
Openalex Percentile: Top 67%
Statistical Distribution Estimation and Applications
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