TY - JOUR
T1 - A Flexible Extension of Pareto Distribution
T2 - Properties and Applications
AU - Alshanbari, Huda M.
AU - Abd Al-Aziz Hosni El-Bagoury, Al-Aziz Hosni El-Bagoury
AU - Gemeay, Ahmed M.
AU - Hafez, E. H.
AU - Eldeeb, Ahmed Sedky
N1 - Publisher Copyright:
© 2021 Huda M. Alshanbari et al.
PY - 2021
Y1 - 2021
N2 - This paper introduced a relatively new mixture distribution that results from a mixture of Fréchet-Weibull and Pareto distributions. Some properties of the new statistical model were derived, such as moments with their related measures, moment generating function, mean residual life function, and mean deviation. Furthermore, different estimation methods were introduced for determining the unknown parameters of the proposed model. Finally, we introduced three real data sets which were applied to our distribution and compared them with other well-known statistical competitive models to show the superiority of our model for fitting the three real data sets, and we can clearly see that our distribution outperforms its competitors. Also, to verify our results, we carried out the existence and uniqueness test to the log-likelihood to determine whether the roots are global maximum or not.
AB - This paper introduced a relatively new mixture distribution that results from a mixture of Fréchet-Weibull and Pareto distributions. Some properties of the new statistical model were derived, such as moments with their related measures, moment generating function, mean residual life function, and mean deviation. Furthermore, different estimation methods were introduced for determining the unknown parameters of the proposed model. Finally, we introduced three real data sets which were applied to our distribution and compared them with other well-known statistical competitive models to show the superiority of our model for fitting the three real data sets, and we can clearly see that our distribution outperforms its competitors. Also, to verify our results, we carried out the existence and uniqueness test to the log-likelihood to determine whether the roots are global maximum or not.
UR - http://www.scopus.com/inward/record.url?scp=85114095274&partnerID=8YFLogxK
U2 - 10.1155/2021/9819200
DO - 10.1155/2021/9819200
M3 - Article
C2 - 34447432
AN - SCOPUS:85114095274
SN - 1687-5265
VL - 2021
JO - Computational Intelligence and Neuroscience
JF - Computational Intelligence and Neuroscience
M1 - 9819200
ER -