pcaL1-package | R Documentation |
This package contains implementations of six principal component analysis methods using the L1 norm. The package depends on COIN-OR Clp version >= 1.17.4. The methods implemented are PCA-L1 (Kwak 2008), L1-PCA (Ke and Kanade 2003, 2005), L1-PCA* (Brooks, Dula, and Boone 2013), L1-PCAhp (Visentin, Prestwich and Armagan 2016), wPCA (Park and Klabjan 2016), and awPCA (Park and Klabjan 2016).
Package: | pcaL1 |
Version: | 1.5.7 |
Date: | 2023-01-16 |
License: | GPL (>=3) |
URL: | http://www.optimization-online.org/DB_HTML/2012/04/3436.html, http://www.coin-or.org |
SystemRequirements: | COIN-OR Clp (>= 1.17.4) |
Index:
awl1pca awPCA l1pca L1-PCA l1pcahp L1-PCAhp l1pcastar L1-PCA* l1projection L1-Norm Projection on a Subspace L2PCA_approx Subroutine for awl1pca l2projection L2-Norm Projection on a Subspace pcal1 PCA-L1 pcalp PCA-Lp pcaL1-package pcaL1: L1-Norm PCA Methods plot.awl1pca Plot an awl1pca Object plot.l1pca Plot an l1pca Object plot.l1pcahp Plot an l1pcahp Object plot.l1pcastar Plot an l1pcastar Object plot.pcal1 Plot a pcal1 Object plot.pcalp Plot a pcalp Object plot.wl1pca Plot an wl1pca Object plot.sharpel1pca Plot a sharpel1pca Object sharpel1pca SharpeEL1-PCA sharpel1rs SharpEl1-RS sparsel1pca SparseEl1-PCA wl1pca wPCA
Sapan Jot <sapan.madaan@gmail.com>, Paul Brooks <jpbrooks@vcu.edu>, Andrea Visentin <andrea.visentin@insight-centre.org>,Young Woong Park <ywpark@mail.smu.edu>, and Yi-Hui Zhou <yihui_zhou@ncsu.edu>
Maintainer: Paul Brooks <jpbrooks@vcu.edu>
Brooks and Dula (2017) Estimating L1-Norm Best-Fit Lines, submitted
Brooks J.P., Dula J.H., and Boone E.L. (2013) A Pure L1-Norm Princpal Component Analysis, Computational Statistics & Data Analysis, 61:83-98. DOI:10.1016/j.csda.2012.11.007
Ke Q. and Kanade T. (2005) Robust L1 Norm Factorization in the Presence of Outliers and Missing Data by Alternative Convex Programming, IEEE Conference on Computer Vision and Pattern Recognition. DOI:10.1109/CVPR.2005.309
Kwak N. (2008) Principal Component Analysis Based on L1-Norm Maximization, IEEE Transactions on Pattern Analysis and Machine Intelligence, 30: 1672-1680. DOI:10.1109/TPAMI.2008.114
Kwak N. (2014) Principal Component Analysis by Lp-Norm Maximization, IEEE Transactions on Cybernetics, 44:594-609. DOI:10.1109/TCYB.2013.2262936
Park, Y.W. and Klabjan, D. (2016) Iteratively Reweighted Least Squares Algorithms for L1-Norm Principal Component Analysis, IEEE International Conference on Data Mining (ICDM). DOI: 10.1109/ICDM.2016.0054
Visentin A., Prestwich S., and Armagan S. T. (2016) Robust Principal Component Analysis by Reverse Iterative Linear Programming, Joint European Conference on Machine Learning and Knowledge Discovery in Databases, 593-605. DOI:10.1007/978-3-319-46227-1_37
Zhou, Y.-H. and Marron, J.S. (2016) Visualization of Robust L1PCA, Stat, 5:173-184. DOI:10.1002/sta4.113
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