Parameters estimation for nonlinear moving average model using Supernova metaheuristic

In the practice, to find the parameters for nonlinear Moving average(NLMA) models is difficult because there are not analytical way to solve maximum likelihood function. In this paper, we compare the parameters estimated for NLMA model with Supernova and PSO-DE algorithm. We found that Supernova estimation is better in terms of a reduction of error and nearest solutions to optimal point.