covPC
(Package: pcaPP) :
Covariance Matrix Estimation from princomp Object
computes the covariance matrix from a princomp object. The number of components k can be given as input.
● Data Source:
CranContrib
● Keywords: multivariate
● Alias: covPC
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PCAgrid
(Package: pcaPP) :
(Sparse) Robust Principal Components using the Grid search algorithm
Computes a desired number of (sparse) (robust) principal components using the grid search algorithm in the plane. The global optimum of the objective function is searched in planes, not in the p-dimensional space, using regular grids in these planes.
● Data Source:
CranContrib
● Keywords: multivariate, robust
● Alias: PCAgrid, sPCAgrid
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qn
(Package: pcaPP) :
scale estimation using the robust Qn estimator
Returns a scale estimation as calculated by the (robust) Qn estimator.
● Data Source:
CranContrib
● Keywords: multivariate, robust
● Alias: qn
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plotcov
(Package: pcaPP) :
Compare two Covariance Matrices in Plots
allows a direct comparison of two estimations of the covariance matrix (e.g. resulting from covPC) in a plot.
● Data Source:
CranContrib
● Keywords: multivariate
● Alias: plotcov
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l1median
(Package: pcaPP) :
Multivariate L1 Median
Computes the multivariate L1 median (also called spatial median) of a data matrix.
● Data Source:
CranContrib
● Keywords: multivariate, robust
● Alias: l1median
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ScaleAdv
(Package: pcaPP) :
centers and rescales data
Data is centered and rescaled (to have mean 0 and a standard deviation of 1).
● Data Source:
CranContrib
● Keywords: multivariate
● Alias: ScaleAdv
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opt.TPO
(Package: pcaPP) :
Model Selection for Sparse (Robust) Principal Components
These functions compute a suggestion for the sparseness parameter lambda which is required by function sPCAgrid. A range of different values for lambda is tested and according to an objective function, the best solution is selected. Two different approaches (TPO and BIC) are available, which is further discussed in the details section. A graphical summary of the optimization can be obtained by plotting the function's return value (plot.opt.TPO, plot.opt.BIC for tradeoff curves or objplot for an objective function plot).
● Data Source:
CranContrib
● Keywords: multivariate, robust
● Alias: opt.BIC, opt.TPO
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data.Zou
(Package: pcaPP) :
Test Data Generation for Sparse PCA examples
Draws a sample data set, as introduced by Zou et al. (2006).
● Data Source:
CranContrib
● Keywords: multivariate, robust
● Alias: data.Zou
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PCAproj
(Package: pcaPP) :
Robust Principal Components using the algorithm of Croux and Ruiz-Gazen (2005)
Computes a desired number of (robust) principal components using the algorithm of Croux and Ruiz-Gazen (JMVA, 2005).
● Data Source:
CranContrib
● Keywords: multivariate, robust
● Alias: PCAproj
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PCdiagplot
(Package: pcaPP) :
Diagnostic plot for principal components
Computes Orthogonal Distances (OD) and Score Distances (SD) for already computed principal components using the projection pursuit technique.
● Data Source:
CranContrib
● Keywords: robust
● Alias: PCdiagplot
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