scholarly journals Estimation of Population Mean In Successive Sampling by Sub-Sampling Non-Respondents

2011 ◽  
Vol 10 (1) ◽  
pp. 51-60 ◽  
Author(s):  
Housila P. Singh ◽  
Sunil Kumar ◽  
Sandeep Bhougal
Keyword(s):  
Successive Sampling ◽  
Population Mean

scholarly journals Successive sampling strategy under non response

2015 ◽  
Vol 11 (1) ◽  
pp. 115-139
Author(s):  
Jaishree Prabha Karna ◽  
Dilip Chandra Nath
Keyword(s):  
Empirical Studies ◽  
Sampling Strategy ◽  
Regression Estimator ◽  
Successive Sampling ◽  
Population Mean ◽  
Successive Rotation ◽  
A Chain ◽  
Chain Type

Abstract The present work is an attempt to study the effect of non-response at both occasions in search of good successive (rotation) sampling over two occasions. A chain-type ratio and regression estimator has been proposed for estimating the population mean at current occasion in presence of non-response at both the occasion in two-occasion successive (rotation) sampling. Detail behaviors of proposed estimators have been studied. Proposed estimators are compared with the estimators for the same situations but in the absence of non-response. Performances of the proposed estimators have been demonstrated via empirical studies.

A General Procedure for Estimating Population Mean in Successive Sampling

2009 ◽  
Vol 38 (2) ◽  
pp. 293-308 ◽  
Author(s):  
Housila P. Singh ◽  
Gajendra K. Vishwakarma
Keyword(s):  
General Procedure ◽  
Successive Sampling ◽  
Population Mean

scholarly journals Estimation of current population mean using two-occasion successive sampling with one auxiliary variable

2018 ◽  
Vol 18 (2) ◽  
pp. 74-77
Author(s):  
R. Zoramthanga
Keyword(s):  
Mean Square Error ◽  
Auxiliary Information ◽  
Auxiliary Variable ◽  
Ratio Estimator ◽  
Mean Square ◽  
Current Estimate ◽  
Successive Sampling ◽  
Population Mean ◽  
Female Workers ◽  
Chain Type

In this study, two-occasion successive sampling for ratio-to-regression estimator was used to determine the current estimate of the population mean using only the matched part and one auxiliary variable, which is available on both the occasions. The data used were based on the total number of female workers in villages in Mizoram with the total number of literate female in villages in Mizoram as an auxiliary variables. The data were gotten from Census of India 2001 and 2011. The optimum mean square error of the combined ratio-to-regression and ratio estimator has been compared with (i) the optimum mean square error of the chain-type ratio estimator (ii) mean per unit estimator and (iii) combined estimator when no auxiliary information is used at any occasion. This result showed that the combined ratio-to-regression and ratio estimator is more efficient than the other three existing estimators.

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