Exploring the New Exponentiated Inverse Weibull Distribution: Properties, Estimation, and Analysis via Classical and Bayesian Approaches

The “New Exponentiated Inverse Weibull” (NEIW) distribution is a novel probability distribution with versatile applications in reliability engineering, survival analysis, and related fields. This study explores the properties of the NEIW distribution, including moments, hazard function behavior, and reliability measures, through rigorous theoretical analysis and simulation studies. Additionally, maximum likelihood estimators (MLEs) for NEIW parameters are investigated via simulation studies to evaluate their performance under various scenarios. Empirical analysis using real-world data sets demonstrates the applicability of the NEIW model in capturing the underlying data structure and extracting meaningful insights. Parameter estimation and analysis are conducted using classical and Bayesian approaches, showcasing the robustness and flexibility of the NEIW distribution. The latest Bayesian analysis software STAN is used to perform the Bayesian analysis using Hamiltonian Monte Carlo (HMC) under No-U-Turn Sampler (NUTS). Overall, this research contributes to the advancement of statistical modeling and analysis by providing a comprehensive framework for utilizing the NEIW distribution in practice, with implications for diverse fields and potential for further exploration and innovation.

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Publication Details

Journal
Contemporary Mathematics
Published
2025-01-22
DOI
https://doi.org/10.37256/cm.6120256255
Citations
2
Primary Topic
Statistical Distribution Estimation and Applications
Type
article
Field-Weighted Citation Impact
5.26
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article

Exploring the New Exponentiated Inverse Weibull Distribution: Properties, Estimation, and Analysis via Classical and Bayesian Approaches

Laxmi Prasad Sapkota, Nirajan Bam, Pankaj Kumar, Vijay Kumar
2 citations
Contemporary Mathematics
Statistical Distribution Estimation and Applications
5.26
article

Exploring the New Exponentiated Inverse Weibull Distribution: Properties, Estimation, and Analysis via Classical and Bayesian Approaches

Laxmi Prasad Sapkota, Nirajan Bam, Pankaj Kumar, Vijay Kumar
article en
2 citations

Abstract

The “New Exponentiated Inverse Weibull” (NEIW) distribution is a novel probability distribution with versatile applications in reliability engineering, survival analysis, and related fields. This study explores the properties of the NEIW distribution, including moments, hazard function behavior, and reliability measures, through rigorous theoretical analysis and simulation studies. Additionally, maximum likelihood estimators (MLEs) for NEIW parameters are investigated via simulation studies to evaluate their performance under various scenarios. Empirical analysis using real-world data sets demonstrates the applicability of the NEIW model in capturing the underlying data structure and extracting meaningful insights. Parameter estimation and analysis are conducted using classical and Bayesian approaches, showcasing the robustness and flexibility of the NEIW distribution. The latest Bayesian analysis software STAN is used to perform the Bayesian analysis using Hamiltonian Monte Carlo (HMC) under No-U-Turn Sampler (NUTS). Overall, this research contributes to the advancement of statistical modeling and analysis by providing a comprehensive framework for utilizing the NEIW distribution in practice, with implications for diverse fields and potential for further exploration and innovation.

Contemporary Mathematics
Tribhuvan University (NP), Miami University (US), Deen Dayal Upadhyaya Gorakhpur University (IN)
Openalex Percentile: Top 7%
Statistical Distribution Estimation and Applications
5.26
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Exploring the New Exponentiated Inverse Weibull Distribution: Properties, Estimation, and Analysis via Classical and Bayesian Approaches — Laxmi Prasad Sapkota, Nirajan Bam, et al. · Contemporary Mathematics (2025) | TGRS Research Map | TGRS