In this paper, a log type calibration estimator for estimating the population mean in stratified random sampling has been proposed utilizing available auxiliary information. This also extended case of double when information is not known. The simulation study carried out using R software on real as well artificial datasets. empirical bootstrap estimates percentage relative root squared error (%...

We propose an improved class of estimators in estimating the nite population variance, using the auxiliary information. The expressions for the bias and mean squared error of the proposed class of estimators are derived up to the rst order of approximation. Some estimators are also derived from a proposed class by allocating the suitable values of known parameters and identi ed as particular me...

In this paper we have proposed a class of ratio-cum-dual to ratio estimators for estimating population variance of the variable under study, using known values of some population parameters of auxiliary variable, which is available in the form of an attribute. The expressions for the bias and mean squared error of the proposed estimators have been derived upto the first order of approximation. ...

In this paper, we have proposed a class of ratio-cum-dual to ratio estimators using known values of some population parameters of the auxiliary variable to estimate the population variance of the study variable. The expressions for the bias and mean square error of the proposed estimators have been derived upto the first order of approximation. A comparison has been made with some well known es...