Comparison of Some Estimation Methods for the Survival Function of the Discrete Inverted Kumaraswamy Distribution.

Abstract

The research examines the Discrete Inverted Kumaraswamy Distribution, which corresponds to the continuous distribution, and estimates the parameters of the studied model using two methods: the Maximum Likelihood Method (MLE) and the Bayes Method. To determine the best estimation method, the Monte Carlo simulation approach was applied using the statistical programming language R (version 4.2.1). The study considered four different cases of model parameters and applied them to three different sample sizes (30, 60, 120) to evaluate the effectiveness of the estimation methods. This evaluation was conducted using the Mean Squared Error (MSE) criterion to compare these methods. The comparison results indicated that the Bayes method was the most effective for small and medium sample sizes in most models. However, for large sample sizes, the Maximum Likelihood Method was found to be superior in most of the models used.