A New Regression Type Estimator with Two Auxiliary Variables for Single-Phase Sampling

Abstract

In this paper, we have proposed an estimator of finite population mean using a new regression type estimator with two auxiliary variables for single-phase sampling and investigated its finite sample properties. An empirical study has been carried out to compare the performance of the proposed estimator with the existing estimators that utilize auxiliary variables for finite population mean. It has been found that the new regression type estimator with two auxiliary variables for to be more efficient than mean per unit, ratio and product estimator and exponential ratio and exponential product estimators and exponential ratio-product estimator.

Modified Regression Type Estimators in the Presence of Non-Response in Two Phase sampling

“…Based on these study results, the proposed estimators 7 t and 8 t are recommended for use in practice when non-response is on the study variable only and on both the study variable and the auxiliary variable in two phase sampling respectively. References…”

“…Kumar and Bhougal (2011) also proposed Exponential ratioproduct estimator when population mean of auxiliary variable X is unknown and non-response occurs in both the study variable and auxiliary variables in two phase sampling. Tum et al (2014) proposed a regression type estimator that combined regression estimator and ratio -product type exponential estimator to form a new modified regression estimator. This study will focus on Tum et al (2014) in presence of non-response in the study variable only and in both the study variable and auxiliary variables and develop their mean squared errors by incorporate Arora and Lal (1989) approach in writing down the mean squared error.…”

“…In addition, the population mean of the auxiliary variable from the previous census may not be available. In this paper, Modified regression type estimators proposed by Tum et al (2014) in single phase sampling, assuming complete response, have been proposed to estimate the population mean of the study variable in the presence of non-response under two phase sampling scheme. The expression of mean squared errors (MSE) based on the proposed estimators have been derived under two phase sampling to the first degree of approximation.…”