Functional outlier detection with robust functional principal component analysis
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- Naveen Narisetty & Xuming He, 2015. "Discussion of “multivariate functional outlier detection”," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 24(2), pages 209-215, July.
- Guochang Wang & Jianjun Zhou & Wuqing Wu & Min Chen, 2017. "Robust functional sliced inverse regression," Statistical Papers, Springer, vol. 58(1), pages 227-245, March.
- Huiwen Wang & Liying Shangguan & Rong Guan & Lynne Billard, 2015. "Principal component analysis for compositional data vectors," Computational Statistics, Springer, vol. 30(4), pages 1079-1096, December.
- Lee, Seokho & Shin, Hyejin & Billor, Nedret, 2013. "M-type smoothing spline estimators for principal functions," Computational Statistics & Data Analysis, Elsevier, vol. 66(C), pages 89-100.
- Bali, Juan Lucas & Boente, Graciela, 2014. "Consistency of a numerical approximation to the first principal component projection pursuit estimator," Statistics & Probability Letters, Elsevier, vol. 94(C), pages 181-191.
- repec:eee:csdana:v:113:y:2017:i:c:p:424-440 is not listed on IDEAS
More about this item
KeywordsFunctional data; Outliers; Principal component analysis; Robust methods;
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