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Small-Area Estimation of Economic Statistics

A ratio-correlation (multiple regression) approach for estimating key economic statistics for small areas is proposed and compared with several synthetic estimation methods using various measures of performance. Using published data that are easily accessible, the methods provide a means of estimating statics not currently published with a reasonable amount of error.

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Variance Estimation Using Auxiliary Information

利用辅助信息进行方差估计

Variance estimators under several sample designs are proposed and compared when auxiliary information is available. Improvement of the bias and mean squared error over some estimators commonly used in practice is illustrated. A Monte Carlo comparison of the estimators is also presented.

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Survey Design under the Regression Superpopulation Model

回归超总体模型下的调查抽样设计

The construction of sample designs and estimators under a linear regression superpopulation model is considered. The anticipated variance, the variance of the predictor computed with respect to the sampling design and the superpopulation model, is used as a criterion for evaluating probability designs and model-unbiased predictors. Regression predictors that are model unbiased and design consistent are constructed.

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Bias of Two Classification Procedures in a Dichotomous Population

二分类总体中两种分类程序的偏差

Two classification procedures are considered in estimating a proportion P in a dichotomous population. Given that classifiers may be subject to error, sufficient conditions are obtained on the probabilities of misclassification of the classifiers such that the bias of one procedure will always be smaller than the bias of the other procedure for typical values of P found in practice. The mean squared error of the former procedure is also shown to be superior for moderate…

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Bias of Two Classification Procedures in a Dichotomous Population

二分类总体中两种分类程序的偏差

Two classification procedures are considered in estimating a proportion P in a dichotomous population. Given that classifiers may be subject to error, sufficient conditions are obtained on the probabilities of misclassification of the classifiers such that the bias of one procedure will always be smaller than the bias of the other procedure for typical values of P found in practice. The mean squared error of the former procedure is also shown to be superior for moderate…

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