Maximum Likelihood Estimates and a survival function for fuzzy data for the Weibull-Pareto parameters

Abstract

In this work, we discuss the estimation parameters and the reliability function for Weibull –Pareto distribution by maximum likelihood method. For that we used two iterative approximation techniques called “Newton-Raphson (NR)” and “Fisher’s Scoring (FS) method” when the available data is in the form of fuzzy numbers. The parameters’ and reliability function’s estimates are numerically contrasted using a Monte-Carlo simulation study in terms of their mean square error (MSE), integrated mean square error (IMSE), and mean absolute proportional error (MAPE) criteria. The FS technique outperforms the NR method in simulations, according to the empirical data.