The choice of the initial estimate for computing MM-estimates
We show, using a Monte Carlo study, that MM-estimates with projection estimates as starting point of an iterative weighted least squares algorithm, behave more robustly than MM-estimates starting at an S-estimate and similar Gaussian efficiency. Moreover the former have a robustness behavior close t...
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| Formato: | Acta de conferencia Capítulo de libro |
| Lenguaje: | Inglés |
| Publicado: |
springer berlin
2008
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| Acceso en línea: | Registro en Scopus Handle Registro en la Biblioteca Digital |
| Aporte de: | Registro referencial: Solicitar el recurso aquí |
| LEADER | 04587caa a22005657a 4500 | ||
|---|---|---|---|
| 001 | PAPER-12892 | ||
| 003 | AR-BaUEN | ||
| 005 | 20230518204305.0 | ||
| 008 | 190411s2008 xx ||||fo|||| 10| 0 eng|d | ||
| 024 | 7 | |2 scopus |a 2-s2.0-84903974279 | |
| 040 | |a Scopus |b spa |c AR-BaUEN |d AR-BaUEN | ||
| 100 | 1 | |a Svarc, M. | |
| 245 | 1 | 4 | |a The choice of the initial estimate for computing MM-estimates |
| 260 | |b springer berlin |c 2008 | ||
| 506 | |2 openaire |e Política editorial | ||
| 504 | |a Davies, L., The asymptotics of S-estimators in the linear regression model (1990) The Annals of Statistics, 18, pp. 1651-1675 | ||
| 504 | |a Donoho, D.L., Huber, P.J., The notion of breakdown-point (1983) A Festschrift for Erich L. Lehmann, pp. 157-184. , P.J. Bickel, K.A. Doksum and J.L Hodges, Jr. (Eds.) Wadsworth, Belmont, California | ||
| 504 | |a Hampel, F.R., A general qualitative definition of robustness (1971) The Annals of Mathematical Statistics, 42, pp. 1887-1896 | ||
| 504 | |a Hossjer, O., On the optimality of S-estimators (1992) Statistics & Probability Letters, 14, pp. 413-419 | ||
| 504 | |a Maronna, R.A., Yohai, V.J., Bias-robust estimates of regression based on projections (1993) The Annals of Statistics, 21, pp. 965-990 | ||
| 504 | |a Maronna, R.A., Martin, R.D., Yohai, V.J., (2006) Robust Statistics: Theory and Methods, , Wiley, Chichister | ||
| 504 | |a Martin, R.D., Yohai, V.J., Zamar, R., Min-max bias robust regression (1989) The Annals of Statistics, 17, pp. 1608-1630 | ||
| 504 | |a Rousseeuw, P.J., Least median of squares regression (1984) J. Am. Stat. Assoc., 79, pp. 871-880 | ||
| 504 | |a Rousseeuw, P.J., Yohai, V.J., Robust regression by means of sestimators (1984) Robust and Nonlinear Time Series, Lecture Notes in Statistics, 26, pp. 256-272. , J. Franke, W. Hardle and R.D. Martin (Eds) Springer-Verlag, Berlin | ||
| 504 | |a Salibian-Barrera, M., Yohai, V.J., A fast algorithm for sregression estimates (2006) Journal of Computational and Graphical Statistics, 15, pp. 414-427 | ||
| 504 | |a Yohai, V.J., High breakdown point and high efficiency robust estimates for regression (1987) The Annals of Statistics, 15, pp. 642-656A4 - et al.; Fundacao para a Ciencia e a Tecnologia (FCT); Instituto Nacional de Estatistica; PORTO Camara Municipal; PSE; Universidade do Porto - Faculdade de Engenharia (FEUP) | ||
| 520 | 3 | |a We show, using a Monte Carlo study, that MM-estimates with projection estimates as starting point of an iterative weighted least squares algorithm, behave more robustly than MM-estimates starting at an S-estimate and similar Gaussian efficiency. Moreover the former have a robustness behavior close to the P-estimates with an additional advantage: they are asymptotically normal making statistical inference possible. |l eng | |
| 593 | |a Departamento de Matemática y Ciencias, Universidad de San Andrés, Vito Dumas 284, 1644 Victoria, Pcia. de Buenos Aires, Argentina | ||
| 593 | |a Departamento de Matemática, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria Pabellón 1, 1426 Buenos Aires, Argentina | ||
| 690 | 1 | 0 | |a P-ESTIMATES |
| 690 | 1 | 0 | |a ROBUST REGRESSION |
| 690 | 1 | 0 | |a S-ESTIMATES |
| 690 | 1 | 0 | |a GAUSSIANS |
| 690 | 1 | 0 | |a INITIAL ESTIMATE |
| 690 | 1 | 0 | |a ITERATIVE-WEIGHTED |
| 690 | 1 | 0 | |a P-ESTIMATES |
| 690 | 1 | 0 | |a ROBUST REGRESSIONS |
| 690 | 1 | 0 | |a S-ESTIMATES |
| 690 | 1 | 0 | |a STATISTICAL INFERENCE |
| 690 | 1 | 0 | |a ITERATIVE METHODS |
| 700 | 1 | |a Yohai, V.J. | |
| 700 | 1 | |a et al.; Fundacao para a Ciencia e a Tecnologia (FCT); Instituto Nacional de Estatistica; PORTO Camara Municipal; PSE; Universidade do Porto - Faculdade de Engenharia (FEUP) | |
| 711 | 2 | |c Porto |d 24 August 2008 through 29 August 2008 |g Código de la conferencia: 106188 | |
| 773 | 0 | |d springer berlin, 2008 |h pp. 503-515 |p COMPSTAT - Proc. Comput. Stat., Symp. |n COMPSTAT 2008 - Proceedings in Computational Statistics, 18th Symposium |z 9783790820836 |t 18th Symposium on Computational Statistics, COMPSTAT 2008 | |
| 856 | 4 | 1 | |u https://www.scopus.com/inward/record.uri?eid=2-s2.0-84903974279&partnerID=40&md5=554524b126abbde36facf1ca08080e2e |y Registro en Scopus |
| 856 | 4 | 0 | |u https://hdl.handle.net/20.500.12110/paper_97837908_v_n_p503_Svarc |y Handle |
| 856 | 4 | 0 | |u https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_97837908_v_n_p503_Svarc |y Registro en la Biblioteca Digital |
| 961 | |a paper_97837908_v_n_p503_Svarc |b paper |c PE | ||
| 962 | |a info:eu-repo/semantics/conferenceObject |a info:ar-repo/semantics/documento de conferencia |b info:eu-repo/semantics/publishedVersion | ||
| 999 | |c 73845 | ||