Generalized Exponential Estimators for Population Variance Under Two-Phase Sampling

Optimal Calibration Estimators under Two-phase Sampling

Multivariate Estimators for Two Phase Sampling

The auxiliary information has always been a source of improvement in estimation of certain population characteristics. Several estimators have been developed in single and two phase sampling which utilizes information on auxiliary variables as well as auxiliary attributes. The classical estimators which use information on auxiliary variables are the ratio and regression estimators as given in H...

An Efficient Class of Chain Estimators of Population Variance under Sub-sampling Scheme

For estimating the population variance S y of study variable y, a class of chain estimators of S y has been proposed in the presence of two auxiliary variables x and z by using known information on population mean and variance of the second auxiliary variable z. In this proposed class, the second auxiliary variable z is directly highly correlated with the first auxiliary variable x, whereas the...

Jackknife Variance Estimation for Two Samples after Imputation under Two-Phase Sampling

We propose a jackknife variance estimator for the population average from two, two-phase samples after imputation. The jackknife method has long been used to estimate and reduce bias, but has now become a valuable tool for variance estimation. We apply two different sampling methods, (simple random sampling and stratified random sampling) to derive jackknife variance estimators for the twosampl...

Computational Approach to Generalized Ratio Type Estimator of Population Mean Under Two Phase Sampling

In the present draft, we propose the computational approach to generalized ratio type estimator of population mean of the main variable under study using auxiliary information. The expressions for the bias and mean square errors (MSE) have been obtained up to the first order of approximation. The minimum value of the MSE of the proposed estimator is also obtained for the optimum value of the ch...