The Chain Ratio Estimator and Regression Estimator with Linear Combination of Two Auxiliary Variables

In sample surveys, it is usual to make use of auxiliary information to increase the precision of the estimators. We propose a new chain ratio estimator and regression estimator of a finite population mean using linear combination of two auxiliary variables and obtain the mean squared error (MSE) equ...

Descripción completa

Detalles Bibliográficos
Autor principal: Lu, Jingli
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3832417/
https://www.ncbi.nlm.nih.gov/pubmed/24260537
http://dx.doi.org/10.1371/journal.pone.0081085
_version_ 1782291675527249920
author Lu, Jingli
author_facet Lu, Jingli
author_sort Lu, Jingli
collection PubMed
description In sample surveys, it is usual to make use of auxiliary information to increase the precision of the estimators. We propose a new chain ratio estimator and regression estimator of a finite population mean using linear combination of two auxiliary variables and obtain the mean squared error (MSE) equations for the proposed estimators. We find theoretical conditions that make proposed estimators more efficient than the traditional multivariate ratio estimator and the regression estimator using information of two auxiliary variables.
format Online
Article
Text
id pubmed-3832417
institution National Center for Biotechnology Information
language English
publishDate 2013
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-38324172013-11-20 The Chain Ratio Estimator and Regression Estimator with Linear Combination of Two Auxiliary Variables Lu, Jingli PLoS One Research Article In sample surveys, it is usual to make use of auxiliary information to increase the precision of the estimators. We propose a new chain ratio estimator and regression estimator of a finite population mean using linear combination of two auxiliary variables and obtain the mean squared error (MSE) equations for the proposed estimators. We find theoretical conditions that make proposed estimators more efficient than the traditional multivariate ratio estimator and the regression estimator using information of two auxiliary variables. Public Library of Science 2013-11-18 /pmc/articles/PMC3832417/ /pubmed/24260537 http://dx.doi.org/10.1371/journal.pone.0081085 Text en © 2013 Jingli Lu http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Lu, Jingli
The Chain Ratio Estimator and Regression Estimator with Linear Combination of Two Auxiliary Variables
title The Chain Ratio Estimator and Regression Estimator with Linear Combination of Two Auxiliary Variables
title_full The Chain Ratio Estimator and Regression Estimator with Linear Combination of Two Auxiliary Variables
title_fullStr The Chain Ratio Estimator and Regression Estimator with Linear Combination of Two Auxiliary Variables
title_full_unstemmed The Chain Ratio Estimator and Regression Estimator with Linear Combination of Two Auxiliary Variables
title_short The Chain Ratio Estimator and Regression Estimator with Linear Combination of Two Auxiliary Variables
title_sort chain ratio estimator and regression estimator with linear combination of two auxiliary variables
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3832417/
https://www.ncbi.nlm.nih.gov/pubmed/24260537
http://dx.doi.org/10.1371/journal.pone.0081085
work_keys_str_mv AT lujingli thechainratioestimatorandregressionestimatorwithlinearcombinationoftwoauxiliaryvariables
AT lujingli chainratioestimatorandregressionestimatorwithlinearcombinationoftwoauxiliaryvariables

Ejemplares similares