Higher order representations of the Robbins–Monro process

For quasi-linear regression functions, the Robbins–Monro process X_n is decomposed in a sum of a linear form and a quadratic form both defined in the observation errors. Under regularity conditions, the remainder term is of order O(n^−3/2) with respect to the L_p-norm. If a cubic form is added, the remainder term can be improved up to an order of O(n⁻²). As a corollary the expectation of X_n is expanded up to an error of order O(n⁻²). This is used to correct the bias of X_n up to an error of order O(n^−3/2 log n).