A Three-Parameter Exponential Frechet Distribution: Theory and Application
DOI:
https://doi.org/10.62054/ijdm/0104.10Keywords:
Exponential Frechet Distribution, Maximum likelihood estimation(MLE), ParameterAbstract
A novel three-parameter distribution of the Exponential G-family distribution called the Exponential Frechet Distribution has been proposed. Some properties of the model like moment generating function, characteristic function, quantile function, survival function and hazard function were derived. Bayesian and MLE approach was used to estimate the parameter. The Exponential Frechet Distribution flexibility was demonstrated by both simulation and application to remission time of bladder cancer patients. The results revealed that the Exponential Frechet Distribution yielded a better fit in comparison with other extended distribution.
References
Ahmed, T. F., Ramadan, D. A., and El-Desouky, B. S. (2023). Statistical inference of modified Frechet–Exponential distribution with applications to real-life data. Applied Mathematics and Information Sciences: An International Journal, 17(1), 109-124.
Bourguignon, M., Silva, R. B., and Cordeiro, G. M. (2014). The Weibull-G family of probability distributions. Journal of Data Science, 12, 53-68.
Cordeiro, G. M., Ortega, E. M. M., Popovic, B. V., and Pescim, R. R. (2014). The Lomax generator of distributions: Properties, minification process and regression model. Applied Mathematics and Computation.
El-Bassiouny, A. H., Abdo, N. F., and Shahen, H. S. (2015). Exponential Lomax distribution. International Journal of Computer Applications, 121(24), 24-29. https://doi.org/10.5120/21602-4713
Eraikhuemen, I. B., Bamigbala, O. A., Magaji, U. A., Yakura, B. S., and Manju, K. A. (2020). Bayesian analysis of Weibull-Lindley distribution using different loss functions. Asian Journal of Advanced Research and Reports, 8(4), 28-41.
Ieren, T. G., Oyamakin, S. O., and Chukwu, A. U. (2018). Modeling lifetime data with Weibull-Lindley distribution. Biometrics and Biostatistics International Journal, 7(6), 532-544.
Lemonte, A. J. (2013). A new exponential-type distribution with constant, decreasing, increasing, upside down bathtub and bathtub-shaped failure rate function. Computational Statistics and Data Analysis, 62, 149-170.
Oguntunde, P. E., Balogun, O. S., Okagbue, H. I., and Bishop, S. A. (2015). The Weibull-Exponential Distribution: Its properties and applications. Journal of Applied Science, 15(11), 1305-1311.
Tahir, M. H., Zubair, M., Mansoor, M., Cordeiro, G. M., and Alizadeh, M. (2016). A new Weibull-G family of distributions. Hacettepe Journal of Mathematics and Statistics, 45(2), 629-647.
Zaharim, A., Razali, A. M., Abidin, R. Z., and Sopian, K. (2009). Fitting of statistical distributions to wind speed data in Malaysia. European Journal of Scientific Research, 26(1), 6-12.
Zografos, K., and Balakrishnan, N. (2009). On families of beta- and generalized gamma-generated distributions and associated inference. Statistical Methodology, 6, 344–362.
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