Now showing items 1-10 of 221
On the asymptotic behavior of general projection-pursuit estimators under the common principal components model
(Elsevier Science, 2010-02)
The common principal components model for several groups of multivariate observations assumes equal principal axes among the groups. Robust estimators can be defined replacing the sample variance by a robust dispersion ...
Consistency of a numerical approximation to the first principal component projection pursuit estimator
(Elsevier Science, 2014-11)
We generalize to functional data, the approach given by Croux and Ruiz-Gazen (1996) to compute robust projection-pursuit principal direction estimators, allowing also for smoothness in the estimators. Consistency of the ...
A projection pursuit framework for supervised dimension reduction of high dimensional small sample datasets
The analysis and interpretation of datasets with large number of features and few examples has remained as a challenging problem in the scientific community, owing to the difficulties associated with the curse-of-the-dim ...
Projection Pursuit And Pca Associated With Near And Middle Infrared Hyperspectral Images To Investigate Forensic Cases Of Fraudulent Documents
(Elsevier Science BVAmsterdam, 2017)
Robust functional principal components: A projection-pursuit approach
(Inst Mathematical Statistics, 2011-12)
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 ...
Robust estimators under a functional common principal components model
(Elsevier Science, 2017-09)
When dealing with several populations of functional data, equality of the covariance operators is often assumed even when seeking for a lower-dimensional approximation to the data. Usually, if this assumption does not hold, ...
Influence function of projection-pursuit principal components for functional data
(Elsevier Inc, 2015-01)
In the finite-dimensional setting, Li and Chen (1985) proposed a method for principal components analysis using projection-pursuit techniques. This procedure was generalized to the functional setting by Bali et al. (2011), ...
Projection Pursuit And The Solvability Condition Applied To Constructive Learning
(IEEE, Piscataway, NJ, United States, 1997)