Local Polynomial Regression Estimator of the Finite Population Total under Stratified Random Sampling: A Model-Based Approach
| Autor: | Romanus Odhiambo, George Otieno Orwa, Sarah Pyeye, Charles K. Syengo |
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| Rok vydání: | 2016 |
| Předmět: |
Polynomial regression
Statistics::Theory 05 social sciences 050401 social sciences methods Estimator Local regression 01 natural sciences Nonparametric regression 010104 statistics & probability Efficient estimator 0504 sociology Bayesian multivariate linear regression Statistics Statistics::Methodology 0101 mathematics Minimax estimator Segmented regression Mathematics |
| Zdroj: | Open Journal of Statistics. :1085-1097 |
| ISSN: | 2161-7198 2161-718X |
| DOI: | 10.4236/ojs.2016.66088 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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