The feasible set algorithm for least median of squares regression
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Bibliographic InfoArticle provided by Elsevier in its journal Computational Statistics & Data Analysis.
Volume (Year): 16 (1993)
Issue (Month): 1 (June)
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- Maronna, Ricardo A. & Barrera, Matías Salibian & Yohai, Víctor J., 2000. "Improving bias-robustness of regression estimates through projections," Statistics & Probability Letters, Elsevier, vol. 47(2), pages 149-158, April.
- Hawkins, Douglas M. & Olive, David J., 1999. "Improved feasible solution algorithms for high breakdown estimation," Computational Statistics & Data Analysis, Elsevier, vol. 30(1), pages 1-11, March.
- Mount, David M. & Netanyahu, Nathan S. & Romanik, Kathleen & Silverman, Ruth & Wu, Angela Y., 2007. "A practical approximation algorithm for the LMS line estimator," Computational Statistics & Data Analysis, Elsevier, vol. 51(5), pages 2461-2486, February.
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- Marco Cattaneo & Andrea Wiencierz, 2014. "On the implementation of LIR: the case of simple linear regression with interval data," Computational Statistics, Springer, vol. 29(3), pages 743-767, June.
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- Neath, Andrew A. & Cavanaugh, Joseph E., 2000. "A regression model selection criterion based on bootstrap bumping for use with resistant fitting," Computational Statistics & Data Analysis, Elsevier, vol. 35(2), pages 155-169, December.
- Nunkesser, Robin & Morell, Oliver, 2008. "Evolutionary algorithms for robust methods," Technical Reports 2008,29, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
- Hawkins, Douglas M. & Olive, David, 1999. "Applications and algorithms for least trimmed sum of absolute deviations regression," Computational Statistics & Data Analysis, Elsevier, vol. 32(2), pages 119-134, December.
- Li, Lei M., 2005. "An algorithm for computing exact least-trimmed squares estimate of simple linear regression with constraints," Computational Statistics & Data Analysis, Elsevier, vol. 48(4), pages 717-734, April.
- Hawkins, Douglas M., 1995. "Convergence of the feasible solution algorithm for least median of squares regression," Computational Statistics & Data Analysis, Elsevier, vol. 19(5), pages 519-538, May.
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