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Referencias:

• Bali, J.L., Boente, G., Tyler, D.E., Wang, J.L., Robust functional principal components: A projection-pursuit approach (2011) Ann. Stat., 39, pp. 2852-2882
• Boente, G., Fraiman, R., Discussion on robust principal component analysis for functional data by N. Locantore, J. Marron, D. Simpson, N. Tripoli, J. Zhang and K. Cohen (1999) Test, 8, pp. 28-35
• Boente, G., Fraiman, R., Kernel-based functional principal components (2000) Stat. Prob. Lett., 48, pp. 335-345
• Croux, C., Filzmoser, P., Oliveira, M.R., Algorithms for projection-pursuit robust principal component analysis (2007) Chem. Intell. Lab. Syst., 87, pp. 218-225
• Croux, C., Ruiz-Gazen, A., A fast algorithm for robust principal components based on projection pursuit (1996) Compstat: Proceedings in Computational Statistics, pp. 211-217. , Prat, A. (ed.), Physica-Verlag, Heidelberg
• Croux, C., Ruiz-Gazen, A., High breakdown estimators for principal components: The projection-pursuit approach revisited (2005) J. Multivar. Anal., 95, pp. 206-226
• Cui, H., He, X., Ng, K.W., Asymptotic distribution of principal components based on robust dispersions (2003) Biometrika, 90, pp. 953-966
• Dauxois, J., Pousse, A., Romain, Y., Asymptotic theory for the principal component analysis of a vector random function: Some applications to statistical inference (1982) J. Multivar. Anal., 12, pp. 136-154
• Gervini, D., Robust functional estimation using the spatial median and spherical principal components (2008) Biometrika, 95, pp. 587-600
• Gervini, D., Detecting and handling outlying trajectories in irregularly sampled functional datasets (2009) Ann. Appl. Stat., 3, pp. 1758-1775
• Gervini, D., Outlier detection and trimmed estimation for general functional data (2012) Stat. Sin.
• Hall, P., Hosseini-Nasab, M., On properties of functional principal components analysis (2006) J. R. Stat. Soc. Ser. B, 68, pp. 109-126
• Hall, P., Müller, H.-G., Wang, J.-L., Properties of principal component methods for functional and longitudinal data analysis (2006) Ann. Stat., 34, pp. 1493-1517
• Hubert, M., Vandervieren, E., An adjusted boxplot for skewed distributions (2008) Comput. Stat. Data Anal., 52, pp. 5186-5201
• Hyndman, R.J., Ullah, S., Robust forecasting of mortality and fertility rates: A functional data approach (2007) Comput. Stat. Data Anal., 51, pp. 4942-4956
• Li, G., Chen, Z., Projection-pursuit approach to robust dispersion matrices and principal components: Primary theory and Monte Carlo (1985) J. Am. Stat. Assoc., 80, pp. 759-766
• Locantore, N., Marron, J.S., Simpson, D.G., Tripoli, N., Zhang, J.T., Cohen, K.L., Robust principal components for functional data (With discussion) (1999) Test, 8, pp. 1-73
• Malfait, N., Ramsay, J.O., The historical functional linear model (2003) Can. J. Stat., 31, pp. 115-128
• Pezzulli, S.D., Silverman, B.W., Some properties of smoothed principal components analysis for functional data (1993) Comput. Stat., 8, pp. 1-16
• Rice, J., Silverman, B.W., Estimating the mean and covariance structure nonparametrically when the data are curves (1991) J. R. Stat. Soc. Ser. B, 53, pp. 233-243
• Sawant, P., Billor, N., Shin, H., Functional outlier detection with robust functional principal component analysis (2011) Comput. Stat., 27, pp. 83-102
• Silverman, B.W., Smoothed functional principal components analysis by choice of norm (1996) Ann. Stat., 24, pp. 1-24
• Sun, Y., Genton, M.G., Functional boxplots (2011) J. Comput. Graph. Stat., 20, pp. 316-334
• Tyler, D., A note on multivariate location and scatter statistics for sparse data sets (2010) Stat. Prob. Lett., 80, pp. 1409-1413
• Yao, F., Lee, T.C.M., Penalized spline models for functional principal component analysis (2006) J. R. Stat. Soc. Ser. B, 68, pp. 3-25
• Zhang, J.-T., Chen, J., Statistical inferences for functional data (2007) Ann. Stat., 35, pp. 1052-1079

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