pcaPP v1.9-73
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Robust PCA by Projection Pursuit
Provides functions for robust PCA by projection pursuit. The methods are described in Croux et al. (2006) <doi:10.2139/ssrn.968376>, Croux et al. (2013) <doi:10.1080/00401706.2012.727746>, Todorov and Filzmoser (2013) <doi:10.1007/978-3-642-33042-1_31>.
Functions in pcaPP
| Name | Description | |
| ScaleAdv | centers and rescales data | |
| cor.fk | Fast estimation of Kendall's tau rank correlation coefficient | |
| PCAgrid | (Sparse) Robust Principal Components using the Grid search algorithm | |
| PCAproj | Robust Principal Components using the algorithm of Croux and Ruiz-Gazen (2005) | |
| covPC | Covariance Matrix Estimation from princomp Object | |
| covPCA | Robust Covariance Matrix Estimation | |
| data.Zou | Test Data Generation for Sparse PCA examples | |
| l1median | Multivariate L1 Median | |
| PCdiagplot | Diagnostic plot for principal components | |
| qn | scale estimation using the robust Qn estimator | |
| l1median_NLM | Multivariate L1 Median | |
| objplot | Objective Function Plot for Sparse PCs | |
| opt.TPO | Model Selection for Sparse (Robust) Principal Components | |
| plot.opt.TPO | Tradeoff Curves for Sparse PCs | |
| plotcov | Compare two Covariance Matrices in Plots | |
| No Results! | ||
Vignettes of pcaPP
| Name | ||
| load.package.name.R | ||
| matlab.example.txt | ||
| matlab.rnw | ||
| No Results! | ||
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Details
| Date | 2018-01-04 |
| License | GPL (>= 3) |
| NeedsCompilation | yes |
| Repository | CRAN |
| Packaged | 2018-01-05 06:39:02 UTC; TodorovV |
| Date/Publication | 2018-01-14 18:27:29 UTC |
| imports | mvtnorm |
| Contributors | Peter Filzmoser, Heinrich Fritz, Klaudius Kalcher |
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