scholarly journals Generalized Ratio-cum-Product Estimator for Finite Population Mean under Two-Phase Sampling Scheme

2021 ◽  
Vol 19 (1) ◽  
pp. 2-16
Author(s):  
Gajendra Kumar Vishwakarma ◽  
Sayed Mohammed Zeeshan
Keyword(s):  
Sampling Scheme ◽  
Two Phase ◽  
Phase Sampling ◽  
Product Estimator ◽  
The Mean ◽  
Set Up ◽  
Mean Square Errors ◽  
Linear Regression Estimator ◽  
The Given ◽  
Two Phase Sampling

A method to lower the MSE of a proposed estimator relative to the MSE of the linear regression estimator under two-phase sampling scheme is developed. Estimators are developed to estimate the mean of the variate under study with the help of auxiliary variate (which are unknown but it can be accessed conveniently and economically). The mean square errors equations are obtained for the proposed estimators. In addition, optimal sample sizes are obtained under the given cost function. The comparison study has been done to set up conditions for which developed estimators are more effective than other estimators with novelty. The empirical study is also performed to supplement the claim that the developed estimators are more efficient.

Family of combined-type estimators for population mean using stratified two-phase sampling scheme under non-response

2020 ◽  
Vol 23 (5) ◽  
pp. 915-928
Author(s):  
Manoj K. Chaudhary ◽  
Amit Kumar ◽  
Gautam K. Vishwakarma ◽  
Cem Kadilar
Keyword(s):  
Sampling Scheme ◽  
Two Phase ◽  
Population Mean ◽  
Phase Sampling ◽  
Two Phase Sampling

Estimation of mean in presence of non-response using two phase sampling scheme

2008 ◽  
Vol 51 (3) ◽  
pp. 559-582 ◽  
Author(s):  
Housila P. Singh ◽  
Sunil Kumar
Keyword(s):  
Sampling Scheme ◽  
Two Phase ◽  
Phase Sampling ◽  
Two Phase Sampling

scholarly journals A Study on the Chain Ratio-Type Estimator of Finite Population Variance

2014 ◽  
Vol 2014 ◽  
pp. 1-5 ◽  
Author(s):  
Yunusa Olufadi ◽  
Cem Kadilar
Keyword(s):  
Finite Population ◽  
Numerical Comparison ◽  
Mean Square ◽  
Auxiliary Variables ◽  
Population Variance ◽  
Two Phase ◽  
First Order ◽  
Phase Sampling ◽  
The Mean ◽  
Two Phase Sampling

We suggest an estimator using two auxiliary variables for the estimation of the unknown population variance. The bias and the mean square error of the proposed estimator are obtained to the first order of approximations. In addition, the problem is extended to two-phase sampling scheme. After theoretical comparisons, as an illustration, a numerical comparison is carried out to examine the performance of the suggested estimator with several estimators.

A two-phase sampling scheme and πps designs

2011 ◽  
Vol 141 (5) ◽  
pp. 1646-1654 ◽  
Author(s):  
Thomas Laitila ◽  
Jens Olofsson
Keyword(s):  
Sampling Scheme ◽  
Two Phase ◽  
Phase Sampling ◽  
Two Phase Sampling

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

2018 ◽  
Vol 6 (07) ◽  
Author(s):  
John Kung’u Wanjiru ◽  
Grace Chumba
Keyword(s):  
Single Phase ◽  
Complete Response ◽  
Auxiliary Variable ◽  
Degree Of Approximation ◽  
Sample Survey ◽  
Sampling Scheme ◽  
Two Phase ◽  
Population Mean ◽  
Phase Sampling ◽  
Two Phase Sampling

It is a common experience in sample survey that data cannot always be collected for all units selected in the sample at the first attempt and even after some call-backs. An estimate obtained from such incomplete data may be misleading because of the non-response in the data. 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. A comparison of the proposed estimators with the usual unbiased estimator and existing estimators under two phase sampling scheme have been carried out. The proposed Modified regression type estimators have been found to be the most efficient compared to the existing estimators and they are recommended for use in practice.

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