Large and moderate deviation principles for recursive kernel estimators of a regression function for spatial data defined by stochastic approximation method

Abstract

In the present paper, we are mainly concerned with a family of kernel type estimators based upon spatial data. More precisely, we establish large and moderate deviations principles for the recursive kernel estimators of a regression function for spatial data defined by the stochastic approximation algorithm.