Abstract:
In this thesis, auxiliary information is used to determine an estimator of
nite population total using nonparametric regression under strati ed random
sampling. To achieve this, a model-based approach is adopted by making use
of the local polynomial regression estimation to predict the nonsampled values
of the survey variable. The performance of the proposed estimator is investigated
against some design-based and model-based regression estimators. From
the simulation experiments, the resulting estimator records better results in the
estimation of the nite population total. Generally, use of the proposed estimator
leads to relatively smaller values of relative e ciency compared to other
estimators.
