Using two-phase sampling scheme, we propose a general class of estimators for finite population mean. This class depends on the sample means and variances of two auxiliary variables. The minimum variance bound for any estimator in the class is provided (up to terms of order n-l). It is also proved that there exists at least a chain regression type estimator which reaches this minimum. Finally, it is shown that other proposed estimators can reach the minimum variance bound, i.e. the optimal estimator is not unique.
Optimal estimation for finite population mean in two phase sampling / G. Diana, C. Tommasi. - In: STATISTICAL METHODS & APPLICATIONS. - ISSN 1618-2510. - 1:12(2003), pp. 41-48. [10.1007/s10260-003-0049-z]
Optimal estimation for finite population mean in two phase sampling
C. Tommasi
2003
Abstract
Using two-phase sampling scheme, we propose a general class of estimators for finite population mean. This class depends on the sample means and variances of two auxiliary variables. The minimum variance bound for any estimator in the class is provided (up to terms of order n-l). It is also proved that there exists at least a chain regression type estimator which reaches this minimum. Finally, it is shown that other proposed estimators can reach the minimum variance bound, i.e. the optimal estimator is not unique.Pubblicazioni consigliate
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