Sensitivity study of estimation methods of the two-dimensional autoregressive model.

BRITOS, GRISEL MARIBEL; OJEDA, SILVIA MARÍA

Comodoro Rivadavia

Congreso; VI Congreso de Matemática Aplicada, Computacional e Industrial; 2017

In this paper we present an estimator of the parameters of an AR-2D model that is an extension of anestimator presented for autoregressive models in time series. It uses an auxiliary model (BIP-AR) that limits thepropagation of noise in an AR process. In addition, we present an analysis of the behavior of these new estimator(BMM-2D) and others estimators for the case of AR-2D processes contaminated by Gaussian noise. We also showan application to the image processing obtaining favorable results for our estimator. Computational implementation iscarried out by R statistical software.