日期精度：到日 0 篇 · 到月 9 篇 · 到年 4 篇
整群抽样的最优与稳健策略
This article extends Royall's (1992) results on optimal and robust sampling strategies to cluster sampling. It also gives the lower bound on the model-based variances of best linear unbiased predictors of finite population totals under certain classes of superpopulation models.
This article extends Royall's (1992) results on optimal and robust sampling strategies to cluster sampling. It also gives the lower bound on the model-based variances of best linear unbiased predictors of finite population totals under certain classes of superpopulation models.
有限总体抽样中稳健估计的若干结果
The present article examines the robustness of sampling strategies, that is, estimators and sample designs, from the point of view of attaining the minimum value of the Godambe—Joshi lower bound to the expected variance of a strategy. It is shown that asymptotic design unbiasedness is necessary but insufficient for robustness defined in the above sense. The concepts of weak and strong robustness of estimators, for given sampling strategies, are introduced. The article…
模型预测与设计估计能够协调到何种程度？
Two general linear model-based predictors, one of the expectation of a finite population total and one of that total itself, are compared with the design-based generalized regression estimator (GRE). First, the predictors are made to conform to the GRE by modifying the regression parameter estimators but retaining the same (optimal) inclusion probabilities. Second, the GRE is made to conform with each of the predictors in turn by modifying the inclusion probabilities but…
有限总体抽样中稳健估计的若干结果
The present article examines the robustness of sampling strategies, that is, estimators and sample designs, from the point of view of attaining the minimum value of the Godambe—Joshi lower bound to the expected variance of a strategy. It is shown that asymptotic design unbiasedness is necessary but insufficient for robustness defined in the above sense. The concepts of weak and strong robustness of estimators, for given sampling strategies, are introduced. The article…
调查抽样中的渐近设计无偏预测量
A probability sampling plan is suggested in this paper for drawing the sample so that the linear least-squares predictor of the total of a finite population is made asymptotically design-unbiased. Conditions are given for the sampling plan to reduce to the more familiar sample designs discussed in the literature.
调查抽样中渐近设计无偏的预测量
A probability sampling plan is suggested in this paper for drawing the sample so that the linear least-squares predictor of the total of a finite population is made asymptotically design-unbiased. Conditions are given for the sampling plan to reduce to the more familiar sample designs discussed in the literature.
高斯超总体模型下 Royall 预测量的最优性
This note shows that under the assumption of a Gaussian superpopulation model with a general symmetric and positive-definite covariance matrix, the model-based predictor of Royall (1976) is the unbiased minimum mean squared error predictor of the total of a given finite population. This somewhat anticipated result is a generalization of recent published work in which it was derived under more restrictive assumptions.
高斯超总体模型下 Royall 预测量的最优性
This note shows that under the assumption of a Gaussian superpopulation model with a general symmetric and positive-definite covariance matrix, the model-based predictor of Royall (1976) is the unbiased minimum mean squared error predictor of the total of a given finite population. This somewhat anticipated result is a generalization of recent published work in which it was derived under more restrictive assumptions.
调查抽样中最优模型预测量的刻画
This paper presents the necessary and sufficient conditions for the optimality of an arbitrary linear predictor of the total of a finite population in survey sampling under a general linear model with a symmetric and positive-definite covariance matrix. Results of the paper extend and unify earlier work on robust estimation in survey sampling under more restrictive conditions.
调查抽样中最优模型预测量的刻画
This paper presents the necessary and sufficient conditions for the optimality of an arbitrary linear predictor of the total of a finite population in survey sampling under a general linear model with a symmetric and positive-definite covariance matrix. Results of the paper extend and unify earlier work on robust estimation in survey sampling under more restrictive conditions.
回归超总体模型下调查抽样的最优估计
The necessary and sufficient conditions for an estimator-design pair to be optimum under a regression superpopulation model with correlated residuals are established. It is shown that some earlier optimality results can be deduced as special cases of the more general model considered in this note.
回归超总体模型下调查抽样的最优估计
The necessary and sufficient conditions for an estimator-design pair to be optimum under a regression superpopulation model with correlated residuals are established. It is shown that some earlier optimality results can be deduced as special cases of the more general model considered in this note.