Dual to Ratio-Cum-Product Estimator in Simple and Stratified Random Sampling

Improvement in Estimating The Population Mean Using Dual To Ratio-Cum-Product Estimator in Simple Random Sampling

A Ratio-cum-Dual to Ratio Estimator of Population Variance Using Qualitative Auxiliary Information Under Simple Random Sampling

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. ...

Dual to Ratio cum Product Estimators of Finite Population Mean Using Auxiliary Attribute(s) in Stratified Random Sampling

The problem of estimating the population mean in un-stratified sampling strategies to estimate the finite the presence of an auxiliary variable has been widely discussed in finite population sampling literature [1], suggested a class of estimators of the population mean using one auxiliary variable in the stratified random sampling and examined the MSE of the estimators up to the kth order of a...

Improved Exponential Estimator in Stratified Random Sampling

In this article we have considered the problem of estimating the population mean   Y in the stratified random sampling using the information of an auxiliary variable x which is correlated with y and suggested improved exponential ratio estimators in the stratified random sampling. The mean square error (MSE) equations for the proposed estimators have been derived and it is shown that the prop...

Scalable Simple Random Sampling and Stratified Sampling

Analyzing data sets of billions of records has now become a regular task in many companies and institutions. In the statistical analysis of those massive data sets, sampling generally plays a very important role. In this work, we describe a scalable simple random sampling algorithm, named ScaSRS, which uses probabilistic thresholds to decide on the fly whether to accept, reject, or wait-list an...