Before revision:  First, we propose adaptive-fitting as a variant of sample-splitting for showing an asymptotically normal semiparametric estimator from dependent samples without non-Donsker nuisance estimators . Second, we report an empirical paradox that a DR estimator shows better performances than other estimators using the true logging policy instead of its estimator .
After revision:  First, we propose adaptive-fitting as a variant of sample-splitting for showing an asymptotically normal semiparametric estimator from dependent samples without non-Donsker nuisance estimators , we propose adaptive-fitting as a variant of sample-splitting. We also report an empirical paradox that a DR estimator shows better performances than other estimators using the true logging policy instead of its estimator .