In sample surveys, it is usual to make use of auxiliary information to increase the precision of estimators. Two classes of estimators are suggested to estimate the population mean for the variable of interest using two auxiliary variables. Some special cases of these two classes of estimators are considered and compared using real data set and computer simulation. It turns out that the newly suggested estimators dominate all other well-known estimators in terms of mean square error and bias. Finally we showed how to extend the two classes of estimators if more than two auxiliary variables are available.
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