Influence function of projection-pursuit principal components for functional data
نویسندگان
چکیده
منابع مشابه
Robust Functional Principal Components : a Projection - Pursuit Approach
In many situations, data are recorded over a period of time and may be regarded as realizations of a stochastic process. In this paper, robust estimators for the principal components are considered by adapting the projection pursuit approach to the functional data setting. Our approach combines robust projection–pursuit with different smoothing methods. Consistency of the estimators are shown u...
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Principal Component Analysis is a technique often found to be useful for identifying structure in multivariate data. Although it has various characterizations (Rao 1964), the most familiar is as a variance-maximizing projection. Projection pursuit is a methodology for selecting low-dimensional projections of multivariate data by the optimization of some index of \interestingness" over all proje...
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Different algorithms for principal component analysis (PCA) based on the idea of projection pursuit are proposed. We show how the algorithms are constructed, and compare the new algorithms with standard algorithms. With the R implementation pcaPP we demonstrate the usefulness at real data examples. Finally, it will be outlined how the algorithms can be used for robustifying other multivariate m...
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ژورنال
عنوان ژورنال: Journal of Multivariate Analysis
سال: 2015
ISSN: 0047-259X
DOI: 10.1016/j.jmva.2014.09.004