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has been cited by the following article:

• TITLE: Local Polynomial Regression Estimator of the Finite Population Total under Stratified Random Sampling: A Model-Based Approach

  AUTHORS: Charles K. Syengo, Sarah Pyeye, George O. Orwa, Romanus O. Odhiambo

  KEYWORDS: Sample Surveys, Stratified Random Sampling, Auxiliary Information, Local Polynomial Regression, Model-Based Approach, Nonparametric Regression

  JOURNAL NAME: Open Journal of Statistics, Vol.6 No.6, December 8, 2016

  ABSTRACT: In this paper, auxiliary information is used to determine an estimator of finite population total using nonparametric regression under stratified 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 y. The performance of the proposed estimator is investigated against some design-based and model-based regression estimators. The simulation experiments show that the resulting estimator exhibits good properties. Generally, good confidence intervals are seen for the nonparametric regression estimators, and use of the proposed estimator leads to relatively smaller values of RE compared to other estimators.