Approximation of the Sum of Independent Lognormal Variates using Lognormal Distribution by Maximum Likelihood Estimation Approached

Three methods of approximating the sum lognormal variates to a distribution were studied. They Wilkinson approximation, Monte Carlo version approximation and using estimated maximum likelihood parameters. The generated empirically simulation based on several conditions such as number in sum, sample points variates, are independent identically distributed (IID) also not (NIID) with Evaluation all three was performed Anderson Darling test. Results show that parameters produced Type I errors close 0.05 target is considered best approximation.