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Estimation of Population Mean in Post-Stratified Sampling Using Known Value of Some Population Parameter(S)

100%
Onyeka A. C.
Statistics in Transition new series
|
2012
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vol. 13
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issue 1
65-78
EN
Following Khoshnevisan et.al. (2007) and Koyuncu and Kadilar (2009), this paper develops a general family of combined estimators of the population mean in post-stratified sampling (PSS) scheme, using known values of some population parameters of an auxiliary variable. Properties of the proposed family of estimators, including conditions for optimal efficiency, are obtained up to first order approximations. The results are illustrated empirically.
2
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On Efficient Difference Type Estimators

88%
Swain A. K. P. C.
Statistics in Transition new series
|
2010
|
vol. 11
|
issue 3
128-135
EN
This paper considers a more efficient difference type estimator in a finite population set-up. Ratio type and regression type estimators are derived as special cases. Further efficiencies of these estimators are compared with classical ratio and regression estimators. Numerical illustrations are provided to compare efficiencies of different competitive estimators.
3
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Bootstrap Method with Calibration for Standard Error Estimators of Income Poverty Measures

75%
Zięba-Pietrzak A., Kordos J., Wieczorkowski R.
Statistics in Transition new series
|
2011
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vol. 12
|
issue 1
81-96
EN
The authors begin with calibration approach in sample surveys, focussing on the Eurostat approach. Next, the indicators of poverty and social exclusion are discussed as an essential tool for monitoring progress in the reduction of these problems. Most of these indicators are calculated according to the Eurostat recommendations, using data from European Statistics on Income and Living Conditions (EU-SILC). Complex sample design of the EU-SILC requires weighted analyses for estimates of population parameters and approximate methods of standard error estimation. In our study McCarthy and Snowden (1985) bootstrap method for standard errors estimation of income poverty measures is presented. In the next step the reweighting of bootstrap weights is applied and results of such calibration are discussed.
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