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has been cited by the following article:

• TITLE: Kumaraswamy-Odd Rayleigh-G Family of Distributions with Applications

  AUTHORS: Jamilu Yunusa Falgore, Sani Ibrahim Doguwa

  KEYWORDS: Odd Rayleigh-G Family, Kumuraswamy Odd Rayleigh-G Family, Kumuraswamy Odd Rayleigh-Loglogistic Distribution, Monte Carlo Simulation, Skewness

  JOURNAL NAME: Open Journal of Statistics, Vol.10 No.4, August 31, 2020

  ABSTRACT: We propose a new generator of continuous distributions with at least four positive parameters called the Kumaraswamy-Odd Rayleigh-G family. Some special cases were presented. The plots of the Kumaraswamy Odd Rayleigh Log-Logistic (KORLL) distribution indicate that the distribution can take many shapes depending on the parameter values. The negative skewness and kurtosis indicates that the distribution has lighter tails than the normal distribution. The Monte Carlo simulation results indicate that the estimated biases decrease when the sample size increases. Furthermore, the root mean squared error estimates decay towards zero as the sample size increases. This part shows the consistency of the maximum likelihood estimators. From the considered analytical measures, the new KORLL provides the best fit to the analysed five real data sets indicating that this new model outclasses its competitors.