The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Statistical Robustness: One View of its use in Applications Today
Abstract
Users of statistical packages need to be aware of the influence that outlying data points can have on their statistical analyses. Robust procedures provide formal methods to spot these outliers and reduce their influence. Although a few robust procedures are mentioned in this article, one is emphasized; it is motivated by maximum likelihood estimation to make it seem more natural. Use of this procedure in regression problems is considered in some detail, and an approximate error structure is stated for the robust estimates of the regression coefficients. A few examples are given. A suggestion of how these techniques should be implemented in practice is included.
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Cites
Robust estimation of a location parameter
Huber, P. J. (1964) · The Annals of Mathematical Statistics · doi:10.1214/aoms/1177703732 · Cited by 7,228
Robust regression using iteratively reweighted least-squares.
Holland, P. W., & Welsch, R. E. (1977) · Communications in Statistics - Theory and Methods · doi:10.1080/03610927708827533 · Cited by 2,115
NON-NORMALITY AND TESTS ON VARIANCES
BOX, G. E. P. (1953) · Biometrika · doi:10.1093/biomet/40.3-4.318 · Cited by 1,302
Cited by
Robust techniques for signal processing: A survey
Kassam, S. A., & Poor, H. V. (1985) · Proceedings of the IEEE · doi:10.1109/proc.1985.13167 · Cited by 815
Outliers and influential data points in regression analysis.
Stevens, J. P. (1984) · Psychological Bulletin · doi:10.1037//0033-2909.95.2.334 · Cited by 465
A Note on Computing Robust Regression Estimates via Iteratively Reweighted Least Squares
Street, J. O., Carroll, R. J., & Ruppert, D. (1988) · The American Statistician · doi:10.1080/00031305.1988.10475548 · Cited by 362
Metadata
- Authors
- Hogg, R. V.
- Venue
- The American Statistician
- Publisher
- Informa UK Limited
- Published
- 1979-08
- Volume
- 33
- Issue
- 3
- Pages
- 108-115
- ISSN
- 0003-1305 (ISSN-L)
- 1537-2731
- OpenAlex
- W2072363142
- Cited by
- 173
- References
- 3
- FWCI
- 4.67
- 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.
