The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Robust Estimation in Finite Populations I
Abstract
This is an application of a least-squares prediction approach to finite population sampling theory. One way in which this approach differs from the conventional one is its focus on characteristics of particular samples rather than on plans for choosing samples. Here we study samples in which many superpopulation models lead to the same optimal (BLU) estimator. Random sampling is considered in the light of these results.
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Cites
Neyman, J. (1934) · Journal of the Royal Statistical Society · doi:10.2307/2342192 · Cited by 1,086
Neyman, J. (1992) · Springer Series in Statistics · doi:10.1007/978-1-4612-4380-9_12 · Cited by 932
Cited by
An Evaluation of Model-Dependent and Probability-Sampling Inferences in Sample Surveys
Hansen, M. H., Madow, W. G., & Tepping, B. J. (1983) · Journal of the American Statistical Association · doi:10.1080/01621459.1983.10477018 · Cited by 366
Models for Nonresponse in Sample Surveys
Little, R. J. A. (1982) · Journal of the American Statistical Association · doi:10.1080/01621459.1982.10477792 · Cited by 278
CASSEL, C. M., SÄRNDAL, C. E., & WRETMAN, J. H. (1976) · Biometrika · doi:10.1093/biomet/63.3.615 · Cited by 276
Efficient balanced sampling: The cube method
Deville, J.-C. (2004) · Biometrika · doi:10.1093/biomet/91.4.893 · Cited by 275
Metadata
- Authors
- Royall, R. M., & Herson, J.
- Venue
- Journal of the American Statistical Association
- Publisher
- Informa UK Limited
- Published
- 1973-12
- Volume
- 68
- Issue
- 344
- Pages
- 880-889
- ISSN
- 0162-1459 (ISSN-L)
- 1537-274X
- OpenAlex
- W2003778856
- Cited by
- 243
- References
- 2
- FWCI
- 4.91
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
