A MASTER'S THESIS AT THE UNIVERSITY OF BASRAH DISCUSSES THE ESTIMATION OF THE RISK FUNCTION TO DISTRIBUTION (MARSHALL-OLIKEN EXTENDED INVERTED KUMARASWAMY) WITH APPLICATION

A MASTER'S THESIS AT THE UNIVERSITY OF BASRAH DISCUSSES THE ESTIMATION OF THE RISK FUNCTION TO DISTRIBUTION (MARSHALL-OLIKEN EXTENDED INVERTED KUMARASWAMY) WITH APPLICATION:
On Wednesday 7/12/2022 the College of Administration and Economics at the University of Basrah discussed a master's thesis in the Statistics Department on (estimating the risk function for the distribution of (Marshall-Oliken Extended Inverted Kumaraswamy) with the application.
The researcher's thesis (Hajar Abd al-Hasan Mohan al-Salihi) aims to estimate the reliability and risk functions of the (Marshall-Oliken Extended Inverted Kumaraswamy) distribution using six methods (the method of greatest possibility mel, the method of least squares ols, the method of estimating the minimum distance cvm, and the method of Jack Nayef for the above-mentioned methods) as well as an estimate Distribution parameters (MOElkum) by the previous methods.
The thesis concluded that the experimental side explained that the method of greatest possibility is the best because it has the least mean square error (MSE) and (IMSE) from the rest of the other estimators, and that the tests of good fit (And., Cra., K-S.) have proven the suitability of the real data for the distribution (MOEIkum).  ) which had the lowest value of good fit criteria (AIC, AICc, BIC) with comparison with (Ikum) distribution, and this confirms the theoretical conclusion that stipulates the preference of composite probabilistic models over the probabilistic models that form them.