Robust Estimation in Finite Populations I
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Publication:5180199
DOI10.2307/2284516zbMath0272.62005OpenAlexW4236474724MaRDI QIDQ5180199
Publication date: 1973
Full work available at URL: https://doi.org/10.2307/2284516
Related Items (28)
Finding optimal estimators in survey sampling using unbiased estimators of zero ⋮ On the prediction of means in a finite population ⋮ Design-based or Prediction-based Inference? Stratified Random vs Stratified Balanced Sampling ⋮ Estimating the total of a continuous population ⋮ Estimation under linear regression models ⋮ Conditional inference in finite population sampling under a calibration model ⋮ Mem squared error estimation in finite populations under nonlinear models ⋮ A fast algorithm for balanced sampling ⋮ Model-based design in small area estimation ⋮ Statistical inference from finite population samples: A critical review of frequentist and Bayesian approaches ⋮ Admissible prediction in superpopulation models with random regression coefficients under matrix loss function ⋮ Corrado Gini, a pioneer in balanced sampling and inequality theory ⋮ Optimal sampling design under the response homogeneous group response mechanism -- a prediction approach ⋮ Asymptotically design-unbiased predictors for two-stage sampling ⋮ Optimal prediction in finite populations under matrix loss ⋮ A review of optimal designs in survey sampling ⋮ Bayes Prediction for a Stratified Regression Superpopulation Model Using Balanced Loss Function ⋮ Finite-population prediction under error-in-variables superpopulation models ⋮ Systematic sampling for autocorrelated superpopulations ⋮ A note on balanced cluster sampling ⋮ Admissible Linear Predictors in the Superpopulation Model with Respect to Inequality Constraints ⋮ A two-way classification of regression estimation strategies in probability sampling ⋮ Systematic and nonrandom sampling in the presence of polynomial trends ⋮ Bayes and minimax prediction in finite populations ⋮ Regression analysis and random sampling ⋮ A statistic for measuring the balance of a sample ⋮ On the optimality of balanced sampling ⋮ Linear least squares estimates and nonlinear means
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