On the parameter estimation of first order IMA model corrupted with white noise

Abstract

In this paper, we showed how the autocovariance functions can be used to estimate the true parameters of IMA(1) models corrupted with white noise . We performed simulation studies to demonstrate our findings. The simulation studies showed that under the presence of errors in not more than 30% of total data points, our method will very closely estimate the true parameter of the process.

Global Jouranl of Mathematical Sciences Vol. 6 (1) 2007: pp. 17-20