Utilising bivariate auxiliary information for enhanced estimation of population mean under simple and stratified random sampling schemes

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.

Improvement in estimating the population mean in simple random sampling using information on auxiliary attribute

This paper proposes some estimators for the population mean by adapting the estimator in Singh et al. (2008) [5] to the ratio estimators presented in Kadilar and Cingi 2006 [2]. We obtain mean square error (MSE) equation for all proposed estimators, and show that all proposed estimators are always more efficient than ratio estimator in Naik and Gupta (1996) [3], and Singh et al. (2008) [5]. The...

Improved estimation of population variance using information on auxiliary attribute in simple random sampling

Singh and Kumar (2011) suggested estimators for calculating population variance using auxiliary attributes. This paper proposes a family of estimators based on an adaptation of the estimators presented by Kadilar and Cingi (2004) and Singh et al. (2007), and introduces a new family of estimators using auxiliary attributes. The expressions of the mean square errors (MSEs) of the adapted and prop...

Estimating the Population Mean in Stratified Population using Auxiliary Information under Non-Response

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...