Robust functional principal components for sparse longitudinal data-Reference-Cited by-同舟云学术

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Robust functional principal components for sparse longitudinal data

Published:2021-02-20 Issue:2 Volume:79 Page:159-188
ISSN:0026-1424
Container-title:METRON
language:en
Short-container-title:METRON

Author:

Boente Graciela^ORCID,Salibián-Barrera Matías

Funder

Secretaria de Ciencia y Tecnica, Universidad de Buenos Aires

Fondo para la Investigación Científica y Tecnológica

Ministerio de Economía, Industria y Competitividad, Gobierno de España

Natural Sciences and Engineering Research Council

Publisher

Springer Science and Business Media LLC

Subject

Statistics and Probability

Link

https://link.springer.com/content/pdf/10.1007/s40300-020-00193-3.pdf

Reference57 articles.

1. Bali, J.L., Boente, G.: Principal points and elliptical distributions from the multivariate setting to the functional case. Stat. Prob. Lett. 79, 1858–1865 (2009)

2. Bali, J.L., Boente, G., Tyler, D., Wang, J.L.: Robust functional principal components: a projection-pursuit approach. Ann. Stat. 39, 2852–2882 (2011)

3. Billor, N., Hadi, A., Velleman, P.: BACON: blocked adaptive computationally efficient outlier nominators. Comput. Stat. Data Anal. 34, 279–298 (2000)

4. Boente, G., Fraiman, R.: Robust nonparametric regression estimation. J. Multivar. Anal. 29, 180–198 (1989)

5. Boente, G., Rodriguez, D., Sued, M.: The spatial sign covariance operator: asymptotic results and applications. J. Multivar. Anal. 170, 115–128 (2019)

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