Double Sampling with Partial Information on Auxiliary Variables

1973 ◽  
Vol 68 (344) ◽  
pp. 914-918 ◽  
Author(s):  
Chien-Pai Han
Keyword(s):  
Partial Information ◽  
Double Sampling ◽  
Auxiliary Variables

scholarly journals Use of Auxiliary Variables and Asymptotically Optimum Estimators in Double Sampling

2016 ◽  
Vol 5 (3) ◽  
pp. 55 ◽  
Author(s):  
M. E. Kanwai ◽  
O. E. Asiribo ◽  
A. Isah
Keyword(s):  
Mean Squared Error ◽  
Population Level ◽  
Auxiliary Variable ◽  
Sample Survey ◽  
Comparative Approach ◽  
Double Sampling ◽  
Auxiliary Variables ◽  
Two Phase ◽  
Optimum Estimator ◽  
The Mean

This paper explore the need for exploiting auxiliary variables in sample survey and utilizing asymptotically optimum estimator in double sampling to increase the efficiency of estimators. The study proposed two types of estimators with two auxiliary variables for two phase sampling when there is no information about auxiliary variables at population level. The expressions for the Mean Squared Error (MSE) of the proposed estimators were derived to the first order of approximation. An empirical comparative approach of the minimum variances and percent relative efficiency were adopted to study the efficiency of the proposed and existing estimators. It was established that, the proposed estimators performed more efficiently than the mean per unit estimator and other previous estimators that don’t use auxiliary variable and that are not asymptotically optimum. Also, it was established that estimators that are asymptotically optimum that utilized single auxiliary variable are more efficient than those that are not asymptotically optimum with two auxiliary variables.

scholarly journals IMPROVEMENT ON ESTIMATING MEDIAN FOR FINITE POPULATION USING AUXILIARY VARIABLES IN DOUBLE-SAMPLING

2018 ◽  
Vol 80 (5) ◽  
Author(s):  
Muhammad Aamir ◽  
Ani Shabri ◽  
Muhammad Ishaq
Keyword(s):  
Relative Efficiency ◽  
Finite Population ◽  
Real Data ◽  
Simple Random Sampling ◽  
Double Sampling ◽  
Data Sets ◽  
Auxiliary Variables ◽  
Theoretical Comparison ◽  
Graphical Comparison ◽  
Replacement Scheme

The aim of the study is to suggest a difference-cum-ratio type of median estimator for finite population median using two-auxiliary variables in double sampling. Using simple random sampling without-replacement scheme (SRSWOR) the estimated mean square error (MSE) and BIAS are computed for the new suggested median estimator. The suggested median estimator has a smaller MSE than all other median estimators currently in practice, showing a valid contribution to the literature. In addition some members of the suggested estimator and theoretical comparison of MSE are also computed. Finally, the numerical and graphical comparison of percent relative efficiency (PRE) is also computed for five different real data sets.

scholarly journals Development of Efficient Estimation Technique for Population Mean in Two Phase Sampling Using Fuzzy Tools

2017 ◽  
Vol 13 (2) ◽  
pp. 5-28 ◽  
Author(s):  
P. Parichha ◽  
K. Basu ◽  
A. Bandyopadhyay ◽  
P. Mukhopadhyay
Keyword(s):  
Natural Population ◽  
Efficient Estimation ◽  
Double Sampling ◽  
Estimation Technique ◽  
Auxiliary Variables ◽  
Two Phase ◽  
Data Set ◽  
Population Mean ◽  
Phase Sampling ◽  
Two Phase Sampling

Abstract The present investigation deals with the problem of estimation of population mean in two-phase (double) sampling. Utilizing information on two auxiliary variables, one chain exponential ratio and regression type estimator has been proposed and its properties are studied under two different structures of twophase sampling. To make the estimator practicable, unbiased version of the proposed strategy has also been developed. The dominance of the suggested estimator over some contemporary estimators of population mean has been established through numerical illustrations carried over the data set of some natural population and artificially generated population. Categorization of the dominance ranges of the proposed estimation strategies are deployed through defuzzification tools, which are followed by suitable recommendations.

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