Some results about averaging in stochastic approximation

The paper presents some results concerning the averaging approach in a ‘general’ linear regression model in one dimension under suitable conditions about the martingale structure of errors. At first asymptotics of the primary and averaged estimators are discussed. Then it is shown that variances of estimators can be consistently estimated by appropriate integrated squared deviations functionals. Finally applications to the construction of confidence regions are considered.