Finite Population Variance Estimation in Presence of Measurement Errors

Abstract

In this article, we propose a class of estimators for the population variance of a quantity of interest. The estimators in the class use auxiliary information to improve efficiency, and we suppose that measurement errors are present both in the study and auxiliary variate. We take into account such problem using a regression approach. We show that the class proposed is quite flexible and general, allowing to consider many kinds of information as auxiliary one. Comparisons within estimators in the class are studied theoretically and through simulations.

Keywords:

• Auxiliary information
• Measurement errors
• Regression
• Semi-partial correlation coefficient

2000 Mathematics Subject Classification:

• 6-xx
• 62D05