Exponential estimators of finite population variance in simple random sampling

2015 ◽  
Author(s):  
Nursel Koyuncu
Keyword(s):  
Random Sampling ◽  
Finite Population ◽  
Simple Random Sampling ◽  
Population Variance

Investigation of Accuracy of a Calibrated Estimator of a Ratio by Modelling

2005 ◽  
Vol 10 (4) ◽  
pp. 333-342
Author(s):  
V. Chadyšas ◽  
D. Krapavickaitė
Keyword(s):  
Mean Square Error ◽  
Taylor Series ◽  
Random Sampling ◽  
Finite Population ◽  
Taylor Series Expansion ◽  
Simple Random Sampling ◽  
Population Parameter ◽  
Mean Square ◽  
Parameter Ratio ◽  
Using Data

Estimator of finite population parameter – ratio of totals of two variables – is investigated by modelling in the case of simple random sampling. Traditional estimator of the ratio is compared with the calibrated estimator of the ratio introduced by Plikusas [1]. The Taylor series expansion of the estimators are used for the expressions of approximate biases and approximate variances [2]. Some estimator of bias is introduced in this paper. Using data of artificial population the accuracy of two estimators of the ratio is compared by modelling. Dependence of the estimates of mean square error of the estimators of the ratio on the correlation coefficient of variables which are used in the numerator and denominator, is also shown in the modelling.

Improved Family of Estimators of Population Variance in Simple Random Sampling

2014 ◽  
Vol 9 (2) ◽  
pp. 219-226 ◽  
Author(s):  
Subhash Kumar Yadav ◽  
Cem Kadilar ◽  
Javid Shabbir ◽  
Sat Gupta
Keyword(s):  
Random Sampling ◽  
Simple Random Sampling ◽  
Population Variance

scholarly journals Estimation of Population Variance Using the Coefficient of Kurtosis and Median of an Auxiliary Variable under Simple Random Sampling

2017 ◽  
Vol 07 (06) ◽  
pp. 944-955
Author(s):  
Tonui Kiplangat Milton ◽  
Romanus Otieno Odhiambo ◽  
George Otieno Orwa
Keyword(s):  
Random Sampling ◽  
Simple Random Sampling ◽  
Auxiliary Variable ◽  
Population Variance

Moments without tears in simple random sampling from a finite population

Biometrika ◽  
1974 ◽  
Vol 61 (1) ◽  
pp. 151-154 ◽  
Author(s):  
H. M. FINUCAN ◽  
R. F. GALBRAITH ◽  
M. STONE
Keyword(s):  
Random Sampling ◽  
Finite Population ◽  
Simple Random Sampling

A family of efficient estimators of the finite population mean in simple random sampling

2017 ◽  
Vol 88 (5) ◽  
pp. 920-934 ◽  
Author(s):  
Surya K. Pal ◽  
Housila P. Singh ◽  
Sunil Kumar ◽  
Kiranmoy Chatterjee
Keyword(s):  
Random Sampling ◽  
Finite Population ◽  
Simple Random Sampling ◽  
Population Mean

scholarly journals A Family of Difference-Cum-Exponential Type Estimators for Estimating the Population Variance Using Auxiliary Information in Sample Surveys

2014 ◽  
Vol 1 ◽  
pp. 15-21
Author(s):  
H.S. Jhajj ◽  
Kusam Lata
Keyword(s):  
Linear Regression ◽  
Exponential Type ◽  
Random Sampling ◽  
Sampling Design ◽  
Mean Squared Error ◽  
Auxiliary Information ◽  
Simple Random Sampling ◽  
Double Sampling ◽  
Population Variance ◽  
Squared Error

Using auxiliary information, a family of difference-cum-exponential type estimators for estimating the population variance of variable under study have been proposed under double sampling design. Expressions for bias, mean squared error and its minimum values have been obtained. The comparisons have been made with the regression-type estimator by using simple random sampling at both occasions in double sampling design. It has also been shown that better estimators can be obtained from the proposed family of estimators which are more efficient than the linear regression type estimator. Results have also been illustrated numerically as well asgraphically.

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