Compare the two subsets of the family of beta-G distributions with two subsets of the family of distributions Zografos-Balakrishnan- G by using Monte Carlo simulation

Document Type : Original Paper


Deparment of Statistics, Payame Noor University, Thehran, IRAN


In this article we want families beta-G distributions with family Zgrafos-Balakryshnan- G where G is a distribution of power series is a family of distributions using goodness of fit test statistics and risk and exchange rate risk, inverse functions, using monte carlo simulation and two sets actual data comparison and show that beta-G family of distributions model more suitable for distribution of a lifetime.


Main Subjects

[1] Eugene, N., Lee, C. and Famoye, F. (2002). Beta normal distribution and its applications, Communications in Statistics– Theory Methods, 31, 497–512.
[2] Nadarajah, S. and Kotz, S. (2004). The beta Gumbel distribution, MathematicalProblems in Engineering, 10, 323–332.
[3] Lee, C.Famoye, F. and Olumolade, O. (2007).The Beta-Weibull distribution: Some properties and applications to censored data, Journal of Modern Applied Statistical Methods, 6, 173–186.
[4] Barreto-Souza, W., Alessandro, H. S.S. and Cordeiro, G.M.M. (2010). The beta generalized exponential distribution, Journal of Statistical Computation and Simulation,80(2), 159-172.
[5] یعقوب زاده، شهرام؛ شادرخ، علی؛ یارمحمدی، مسعود (1394). چندجمله‌ای‌های استرلینگ و تعمیمی جدید از توزیع وایبول هندسی، علوم آماری، دوره‌ی9، شماره‌ی 1، 119-141.
[6] Zografos, K. and Balakrishnan, N. (2009). On families of beta-and generalized gamma-generated distributions and associated inference, Statistical Methodology, 6, 344–362.
[7] Ramos, M.W.A., Cordeiro, G.M., Marinho, P.R.D., Dias, C.R. B. and Hamedani, G.G. (2013). The Zografos-Balakrishnan Log-Logistic Distribution: Properties and Applications, Communications in Statistics– Theory Methods,12(3), 225-244.
[8] Barreto-Souza, W., de Morais, A.L. and Cordeiro, G.M. (2011). The Weibull-geometric distribution, Journal of Statistical computation and Simulation, 81, 645–657.
[9] Marshall, A.W. and Olkin, I. (1997). A new method for adding a parameter to a family of distributions with application to the exponential and Weibull families, Biometrika, 84, 641–652.
[10] Mahmoudi, E. and Sepahdar, A. (2013). Exponentiated Weibull–Poisson distribution: Model properties and applications, Mathematics and Computers in Simulation, 92, 76–97.
[11] Chen, G. and Balakrishnan, N. (1995). A general purpose approximate goodness-of-fit test, Journal of Quality Technology, 27, 154–161.
[12] Balakrishnan, N., Leiva, V., Sanhueza, A. and Cabrera, E. (2009). Mixture inverse Gaussian distributions and its transformations, Moments and applications, Statistics, 43, 91–104.