<abstract xmlns="http://www.w3.org/1999/xhtml"><p>This article discusses use of the composite estimator with the optimal weight to reduce the variance (or the mean-squared-error, MSE) of the ratio estimator. To study the practical usefulness of the proposed composite estimator, a Monte Carlo simulation is performed comparing the bias and MSE of composite estimators (with estimated optimal weight and with known optimal weight) with those of the simple expansion and the ratio estimators. Two examples, one regarding the estimation of dead fir trees via an aerial photo and the other regarding the estimation of the average sugarcane acres per county, are included to illustrate the use of the composite estimator developed here.</p></abstract>

This article discusses use of the composite estimator with the optimal weight to reduce the variance (or the mean-squared-error, MSE) of the ratio estimator. To study the practical usefulness of the proposed composite estimator, a Monte Carlo simulation is performed comparing the bias and MSE of composite estimators (with estimated optimal weight and with known optimal weight) with those of the simple expansion and the ratio estimators. Two examples, one regarding the estimation of dead fir trees via an aerial photo and the other regarding the estimation of the average sugarcane acres per county, are included to illustrate the use of the composite estimator developed here.

Notes on Use of the Composite Estimator: an Improvement of the Ratio Estimator

Journal of Official Statistics

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"Notes on Use of the Composite Estimator: an Improvement of the Ratio Estimator"}

This article discusses use of the composite estimator with the optimal weight to reduce the variance (or the mean-squared-error, MSE) of the ratio estimator....

Notes on Use of the Composite Estimator: an Improvement of the Ratio Estimator

Online veröffentlicht: 17. März 2020

Seitenbereich: 137 - 149

Eingereicht: 01. Nov. 2018

Akzeptiert: 01. Nov. 2019

DOI: https://doi.org/10.2478/jos-2020-0007

Schlüsselwörter
Composite estimator, ratio estimator, simple expansion estimator, odds ratio, phi correlation, regression estimator

© 2020 Kung-Jong Lui, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Notes on Use of the Composite Estimator: an Improvement of the Ratio Estimator

Online veröffentlicht: 17. März 2020

Seitenbereich: 137 - 149

Eingereicht: 01. Nov. 2018

Akzeptiert: 01. Nov. 2019

DOI: https://doi.org/10.2478/jos-2020-0007

SchlüsselwörterComposite estimator, ratio estimator, simple expansion estimator, odds ratio, phi correlation, regression estimator

© 2020 Kung-Jong Lui, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Schlüsselwörter
Composite estimator, ratio estimator, simple expansion estimator, odds ratio, phi correlation, regression estimator