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Bounds for the Error-Variance of an Estimator in Sampling with Varying Probabilities from a Finite Population

有限总体不等概率抽样中估计量误差方差的上界

This paper presents three upper bounds for the variance of an estimator, based on observations selected with varying probabilities from a finite population, the elements of which are ranked with respect to the Y values. Accordingly, the usefulness of these bounds relates to the pre-enumeration analysis where one may well know the intended probabilities and joint probabilities corresponding to the sampling scheme but does not know the Y values. If, however, one can make a…

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On a Class of Linear Estimators in Sampling with Varying Probabilities without Replacement

不等概率不放回抽样中的一类线性估计量

Horvitz and Thompson [3] have suggested for the estimation of population characteristic certain classes of linear estimators depending on weights associated with the sample observations, when a sample of size n is drawn without replacement using arbitrary probabilities of selection for each draw. However, it should be observed here, that there might not exist even a single linear unbiased estimator for the class which is termed an empty class. A situation arises where the…

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On a Class of Linear Estimators in Sampling With Varying Probabilities Without Replacement

不等概率不放回抽样中的一类线性估计量

Horvitz and Thompson [3] have suggested for the estimation of population characteristic certain classes of linear estimators depending on weights associated with the sample observations, when a sample of size n is drawn without replacement using arbitrary probabilities of selection for each draw. However, it should be observed here, that there might not exist even a single linear unbiased estimator for the class which is termed an empty class. A situation arises where the…

AI 解读阅读原文 ↗BibTeX ↓