Regression Models with Time Series Errors.

In models of the form Y[sub t] = r(X[sub t] ) + Z[sub t] , where r is an unknown function and {X[sub t] } is a covariate process independent of the stationary error {Z[sub t] }, we give conditions under which estimators based on residuals Z[sub 1] , ..., Z[sub n] obtained from linear smoothers are asymptotically equivalent to those based on the actual errors Z[sub 1] , ..., Z[sub n] . [ABSTRACT FROM AUTHOR]