Finally, to demonstrate the utility of the proposed distribution, the model was applied to real-life data sets.
📌 3 Key Takeaways
🎯
Objective & Hypothesis:This article's main emphasis was on the Nakagami Frechet (NF) distribution's generalization.
📊
Key Findings & Data:In this study, theoretical derivations for the probability density function (PDF), cumulative distribution function (CDF), survival, and hazard functions of the NF distribution were derived and discussed.
💡
Conclusion & Impact:Finally, to demonstrate the utility of the proposed distribution, the model was applied to real-life data sets.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Nakagami · Frechet · Quantile Function
Abstract
This article's main emphasis was on the Nakagami Frechet (NF) distribution's generalization. In this study, theoretical derivations for the probability density function (PDF), cumulative distribution function (CDF), survival, and hazard functions of the NF distribution were derived and discussed. Some fundamental mathematical and statistical properties are derived. In addition, the maximum likelihood estimator is used to obtain the model parameters. We present the simulation to evaluate the reliability of maximum likelihood estimators. Finally, to demonstrate the utility of the proposed distribution, the model was applied to real-life data sets.
JOB, O., ABDULLAHİ, İ. (2023). The Nakagami Frechet Distribution in Modeling Real-life Data. Scientific Journal of Mehmet Akif Ersoy University, Cilt: 6 Sayı: 1, 1–10. https://ajindex.com/articles/946739
Nicholas E, Carl L, and Felix F., (2002). Beta-normal distribution and its applications. Communications in Statistics-Theory and methods. Vol. 31, no.4 p. 497-512.
Cordeiro, G.M. and de-Castro, M., (2011). A new family of generalized distributions. Journal of Statistical Computation and Simulation. Vol. 81 p. 883-893.
Alzaatreh, A., Lee, C. and Famoye, F., (2013). A new method for generating families of continuous distributions. Metron. Vol.71, p. 63-79.
Bourguignon, M., Silva, R.B. and Cordeiro, G.M., (2014). The Weibull-G family of probability distribution. Journal of Data Science. Vol. 12, p. 1253-1268.
Hosseini, B., Afshari, M. and Alizadeh, M., (2018). The generalized odd Gamma-G family of distributions: properties and applications. Austrian Journal of Statistics. Vol. 47, p. 69-89.
Ibrahim, A. and Job, O., (2020). The generalized odd Nakagami-G family of distributions: properties and applications. Naturengs MTU Journal of Engineering and Natural Sciences. Vol. 1 no.2 p.1-16.
Ibrahim, A. and Job, O., (2020). A new family of odd generalized Nakagami (Nak-G) distributions. Turkish Journal of Science. Vol. 5 no. 2 p. 85-101.
Mathee, P., Ibrahim, A. and Job, O., (2022). A new family of odd Nakagami Exponential (NE-G) distributions. Journal of New Theory. Vol34 p. 100-118.
Murthy, D. P., Xie, M., and Jiang, R. (2004). Weibull models. John Wiley and Sons. Techno