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Marazzi, A.; Villar, A.J.; Yohai, V.J. "Robust response transformations based on optimal prediction" (2009) Journal of the American Statistical Association. 104(485):360-370
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Abstract:

Nonlinear regression problems can often be reduced to linearity by transforming the response variable (e.g., using the Box-Cox family of transformations). The classic estimates of the parameter defining the transformation as well as of the regression coefficients are based on the maximum likelihood criterion, assuming homoscedastic normal errors for the transformed response. These estimates are nonrobust in the presence of outliers and can be inconsistent when the errors are nonnormal or heteroscedastic. This article proposes new robust estimates that are consistent and asymptotically normal for any unimodal and homoscedastic error distribution. For this purpose, a robust version of conditional expectation is introduced for which the prediction mean squared error is replaced with an M scale. This concept is then used to develop a nonparametric criterion to estimate the transformation parameter as well as the regression coefficients. A finite sample estimate of this criterion based on a robust version of smearing is also proposed. Monte Carlo experiments show that the new estimates compare favorably with respect to the available competitors. © 2009 American Statistical Association.

Registro:

Documento: Artículo
Título:Robust response transformations based on optimal prediction
Autor:Marazzi, A.; Villar, A.J.; Yohai, V.J.
Filiación:Institute for Social and Preventive Medicine, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Bugnon 17, CH 1005 Lausanne, Switzerland
Departamento de Matematicas, Facultad de Ciencias Exactas y Naturales, University of Buenos Aires, Argentina
Palabras clave:Box-cox transformations; Conditional expectation; Heteroscedasticity; Robust estimation; Smearing estimate
Año:2009
Volumen:104
Número:485
Página de inicio:360
Página de fin:370
DOI: http://dx.doi.org/10.1198/jasa.2009.0109
Título revista:Journal of the American Statistical Association
Título revista abreviado:J. Am. Stat. Assoc.
ISSN:01621459
Registro:https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_01621459_v104_n485_p360_Marazzi

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Citas:

---------- APA ----------
Marazzi, A., Villar, A.J. & Yohai, V.J. (2009) . Robust response transformations based on optimal prediction. Journal of the American Statistical Association, 104(485), 360-370.
http://dx.doi.org/10.1198/jasa.2009.0109
---------- CHICAGO ----------
Marazzi, A., Villar, A.J., Yohai, V.J. "Robust response transformations based on optimal prediction" . Journal of the American Statistical Association 104, no. 485 (2009) : 360-370.
http://dx.doi.org/10.1198/jasa.2009.0109
---------- MLA ----------
Marazzi, A., Villar, A.J., Yohai, V.J. "Robust response transformations based on optimal prediction" . Journal of the American Statistical Association, vol. 104, no. 485, 2009, pp. 360-370.
http://dx.doi.org/10.1198/jasa.2009.0109
---------- VANCOUVER ----------
Marazzi, A., Villar, A.J., Yohai, V.J. Robust response transformations based on optimal prediction. J. Am. Stat. Assoc. 2009;104(485):360-370.
http://dx.doi.org/10.1198/jasa.2009.0109