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Using Estimation Methods For the Transformed kappa Distribution
The researcher used the three-parameter Kappa distribution to build a new probability distribution using the quadratic transformation formula, so it becomes the four-parameter Kappa distribution. The distribution properties were studied, extracted, and the distribution was applied to five traditional estimation methods. Among these methods used are the Cramer-Von Mises Minimum method, the Anderson-Darling method, the Anderson-Darling Right-Tail method, and the Anderson-Darling Left-Tail method. In order to find the best method among the estimation methods, the Monte Carlo simulation method was used using the Mathematica12.2 program. The researcher used four models for different sample sizes (small, medium, large). Different values were chosen for the distribution parameters, in order to study the behavior of the measures using the mean square error (MSE). The preference in estimating the parameters was Cramer-Von Mises For small, medium and large sample sizes. The distribution was applied to real data for heart patients. The sample size was (104) observations in weeks representing the patient's survival time until death. Using goodness of fit criteria, the superiority of the transformed distribution was proven compared to the distribution before transformation and other distributions under study.
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