Estimation of the Burr XII Model Parameters Based on Runge-Kutta Method

Abstract

Abstract A new technique has been used for transforming the stationary equation into a differential equation. Thus, the Runge-Kutta method can be used to solve it. This method has been applied to the Burr type-XII model parameters based on a generalized progressive hybrid censoring scheme and compared with maximum likelihood and Bayes methods via Monte Carlo simulations. The simulation results are highly favorable to the Runge-Kutta method, which provides better estimates and outperforms the Bayes and maximum likelihood methods. Finally, two real datasets have been provided to demonstrate the efficiency of the proposed methods.