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有限总体置信区间的条件覆盖性质AI 解读

Standardized errors (Ť — T)/v 1/2 were calculated for both ratio and regression estimators in each of 10,000 simple random samples of n = 32 from each of six populations, using four different variance estimators. Graphs show how the percentage of intervals T ± 1.96 v 1/2 that fail to contain T changes as a function of the average value of the auxiliary variable in the sample. They reveal that (a) intervals using the variance estimators from standard linear regression theory…

有限总体线性回归估计量及其方差估计的经验研究AI 解读

The usual variance estimator for the linear regression estimator of a finite population total is examined under some prediction (superpopulation) models. Its bias is compared with that of the least squares variance estimator. Also described are three bias-robust alternatives, one of which is the jackknife variance estimator. The theoretical results are supported by an empirical study in which simple and restricted random samples as well as some purposive (nonrandom) samples…

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比率估计量及其方差估计量的实证研究AI 解读

This paper reports results from an empirical study of the ratio estimator for a finite population total. From each of six real populations, 1,000 simple random samples, 1,000 restricted random samples, and three nonrandom samples of size 32 are drawn. Performance of the ratio estimator and of five estimators of its variance is compared with theoretical results generated using (a) prediction (superpopulation) models and (b) probability sampling distributions. The results,…

有限总体抽样中的方差估计AI 解读

Under a linear regression model, the best linear unbiased estimator (BLUE) for a finite population total can be obtained. The problem studied here is that of estimating the variance for setting large-sample confidence intervals about the BLUE when the model generating this estimate is inaccurate. A robust variance estimator is derived, and its asymptotic properties are shown to compare favorably with those of the weighted least-squares variance estimator. The robust variance…