A Class of Improved Estimators for Estimating Population Mean Regarding Partial Information in Double Sampling

Authors

  • Aamir Sanaullah

Keywords:

double sampling, auxiliary variable, partial information, bias, mean square error

Abstract

In this paper a class of improved estimators has been proposed for estimating population mean in two phase (double) sampling when only partial information is available on either of two auxiliary variables. Under simple random sampling (SRWOR), expressions of mean square error and bias have been derived to make comparison of suggested class with wide range of other estimators. Empirical study has also been given using five different natural populations. Empirical study confirmed that the suggested class of improved estimators is more efficient under percent relative efficiency (PRE) criterion.

How to Cite

Aamir Sanaullah. (2012). A Class of Improved Estimators for Estimating Population Mean Regarding Partial Information in Double Sampling. Global Journal of Science Frontier Research, 12(F14), 33–45. Retrieved from https://journalofscience.org/index.php/GJSFR/article/view/688

A Class of Improved Estimators for Estimating Population Mean Regarding Partial Information in Double Sampling

Published

2012-12-15