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.
Highlights
Sample surveys’ main objective is to obtain information about the population, and use such information to make inference about some population quantities
Auxiliary information is used to determine an estimator of finite population total using nonparametric regression under stratified random sampling
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
Summary
Sample surveys’ main objective is to obtain information about the population, and use such information to make inference about some population quantities. [14] first considered nonparametric models for ξ within a model-assisted approach and obtained a local polynomial regression estimator as a generalization of the ordinary generalized regression estimator Their simulation study shows that the proposed estimator performs relatively better than other parametric estimators. Stratified estimators for finite population total Y or mean Y have proved to yield better estimators than those resulting from simple random sampling [15] [16] It has been shown in the literature that local polynomial approximation method has several nice features including satisfactory boundary behaviour, easy interpretability, applicability for a variety of design-circumstances and nice minimax properties (see [17] [18] and [19])
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
