ISSN: A/F

Exploring the Beta Linear Failure Rate Geometric Distribution: Properties and Applications

Abstract

This paper introduces the Beta Linear Failure Rate Geometric (BLFRG) distribution, a flexible model that encompasses various well-known distributions as special cases, including the exponentiated linear failure rate geometric, linear failure rate geometric, linear failure rate, exponential geometric, Rayleigh geometric, Rayleigh, and exponential distributions. The BLFRG distribution generalizes the linear failure rate distribution and provides a broader framework for modeling lifetime data. The paper thoroughly investigates the model's properties, including its moments, conditional moments, deviations, Lorenz and Bonferroni curves, and entropy, offering a comprehensive understanding of its behavior. The paper also discusses the estimation methods for the model parameters. To demonstrate its practical utility, the BLFRG distribution is applied to real data examples, showcasing its effectiveness in capturing various patterns in lifetime data. The BLFRG distribution provides a versatile tool for reliability analysis and can be utilized in various applications involving lifetime data with different failure patterns.

References

  1. Khan, M. S. (2010). The Beta Inverse Weibull Distribution. International Transactions in Mathematical Sciences and Computer, 3, 113-119
  2. Lee, C., Famoye, F., Olumolade, O. (2007). Beta-Weibull Distribution: Some Properties and Applications to Censored Data. Journal of Modern Applied Statistical Methods, 6, 173-186
  3. Mahmoudi, E., and Jafari, A. (2014). The Compound Class of Linear Failure Rate-Power Series Distributions: Model, Properties and Applications. arXiv:1402.5282v1 [stat.CO]
  4. Marshall, A. W., and Olkin, I. (2007). Life Distributions: Structure of Nonparametric, Semi parametric and Parametric Families. New York: Springer
  5. Kumar, N. (2024). Innovative Approaches of E-Learning in College Education: Global Experience. E-Learning Innovations Journal, 2(2), 36–51. https://doi.org/10.57125/ELIJ.2024.09.25.03
  6. Dorota Jelonek, Narendra Kumar and Ilona Paweloszek(2024): Artificial Intelligence Applications in Brand Management, S I L E S I A N U N I V E R S I T Y O F T E C H N O L O G Y P U B L I S H I N G H O U S E SCIENTIFIC PAPERS OF SILESIAN UNIVERSITY OF TECHNOLOGY, Serial No 202, pp 153-170
  7. R. Vettriselvan, C. Vijai, J. D. Patel, S. Kumar. R, P. Sharma and N. Kumar (2024): "Blockchain Embraces Supply Chain Optimization by Enhancing Transparency and Traceability from Production to Delivery," International Conference on Trends in Quantum Computing and Emerging Business Technologies, Pune, India, 2024, pp. 1-6, doi: 10.1109/TQCEBT59414.2024.10545308
  8. A. Dodamani, M. A. Sultan Ghori, J. D. Patel, S. K. R, D. Dharamvir and N. Kumar (2024): "Embracing Uncertainty and Approximations for Intelligent Problem-Solving with Soft Computing," International Conference on Trends in Quantum Computing and Emerging Business Technologies, Pune, India, 2024, pp. 1-6, doi: 10.1109/TQCEBT59414.2024.10545184
  9. Balakrishnan, N., & Kundu, D. (2019). Handbook of Exponential Families with Applications. Springer Science & Business Media
Download PDF

How to Cite

Pradeep Upadhyay, (2025-04-14 09:35:28.962). Exploring the Beta Linear Failure Rate Geometric Distribution: Properties and Applications. JANOLI International Journal of Data Science , Volume IvLeBr8hfdwDaPoh7BrK, Issue 1.