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

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.

Author(s):  
Manoj K. Chaudhary ◽  
Amit Kumar

In the present paper, we have proposed some improved ratio and regression-type estimators of the finite population mean utilizing the information on two auxiliary variables in the presence of non-response. The two-phase sampling scheme has been used to accomplish the job of estimating the desired parameter. The expressions for the basic properties such as bias and mean square error (MSE) of the proposed estimators have been derived up to the first order of approximation. A comparative study of the proposed estimators with some existing estimators has also been carried out through a real data set.


2021 ◽  
Vol 6 (12) ◽  
pp. 13592-13607
Author(s):  
Xuechen Liu ◽  
◽  
Muhammad Arslan ◽  

<abstract><p>This article deals with estimation of finite population mean using the auxiliary proportion under simple and two phase sampling scheme utilizing two auxiliary variables. Mathematical expressions for the mean squared errors of the proposed estimators are derived under first order of approximation. We compare the proposed class of estimators "theoretically and numerically" with the usual mean estimator of Naik and Gupta <sup>[<xref ref-type="bibr" rid="b1">1</xref>]</sup>. The theoretical as well as numerical findings support the superiority of our proposed class of estimator as compared to estimators available in literature.</p></abstract>


2019 ◽  
Vol 53 (1) ◽  
pp. 79-91
Author(s):  
P. A. Patel ◽  
F. H. Shah

This paper deals with the estimation of population mean under two-phase sampling. Utilizing information on two-auxiliary variables, a class of estimators for estimating the finite population mean is proposed, and its properties, up to the first order of approximation, are studied. Various estimators are suggested as special cases of this class. The performance of the suggested estimators is compared with some contemporary estimators of population mean through numerical illustrations carried over existing datasets of some natural populations. Also, a small scale Monte Carlo simulation is carried out for the empirical comparison.


2019 ◽  
Vol 25 (2) ◽  
pp. 201-208
Author(s):  
Adamu Isah Kamba ◽  
Amos Adedayo Adewara ◽  
Audu Ahmed

In this paper, modification of product estimator under two-phase sampling was suggested. The modified product estimator was obtained through transformation in two cases using sample mean of auxiliary variables. Case one was when the second sample was drawn from the first sample while case two was when the second sample was drawn from the population. The bias and mean square error (MSE) of the modified product estimator was obtained. The theoretical and numerical validity of the modified product estimator under the two cases were determined to show it superiority to some considered existing product estimators. Numerical results shows that the modified product estimator under the two cases were more efficient than the considered existing estimators.Keywords: Product estimator, Two-Phase Sampling, Bias, Mean Square Error


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