A new estimator for population mean using two auxiliary variables in stratified random sampling

Estimator of a Population Mean Using Two Auxiliary Variables in Simple Random Sampling

We propose a new ratio estimator using two auxiliary variables in simple random sampling. We obtain mean square error (MSE) equation of this estimator and theoretically show that our proposed estimator is more efficient than the traditional multivariate ratio estimator under a defined condition. In addition, we support this theoretical result with the aid of a numerical example.

A New Exponential Type Estimator for the Population Mean in Simple Random Sampling

‎In this paper‎, ‎a new estimate of exponential type of auxiliary information to help simple random sampling without replacement of the finite population mean is introduced‎. ‎This new estimator with a few other estimates using two real data sets are compared with the mean square error‎.

Improved Exponential Estimator for Population Variance Using Two Auxiliary Variables

In this paper exponential ratio and exponential product type estimators using two auxiliary variables are proposed for estimating unknown population variance y S . Problem is extended to the case of two-phase sampling. Theoretical results are supported by an empirical study.

An Improved Suggestion in Stratified Random Sampling Using Two Auxiliary Variables

Improvement in Estimating Population Mean using Two Auxiliary Variables in Two-Phase Sampling

This study proposes improved chain-ratio type estimator for estimating population mean using some known values of population parameter(s) of the second auxiliary character. The proposed estimators have been compared with two-phase ratio estimator and some other chain ratio type estimators. The performances of the proposed estimators have been supported with a numerical illustration.