R Graphical Manual

Last data update: 2014.03.03

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Results 1 - 10 of 82 found.
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PcaHubert-class (Package: rrcov) : Class "PcaHubert" - ROBust method for Principal Components Analysis

The ROBPCA algorithm was proposed by Hubert et al (2005) and stays for 'ROBust method for Principal Components Analysis'. It is resistant to outliers in the data. The robust loadings are computed using projection-pursuit techniques and the MCD method. Therefore ROBPCA can be applied to both low and high-dimensional data sets. In low dimensions, the MCD method is applied.

● Data Source: CranContrib
● Keywords: multivariate, robust
● Alias: PcaHubert-class, getQuan,PcaHubert-method
● 0 images

getLoadings-methods (Package: rrcov) : Accessor methods to the essential slots of Pca and its subclasses

Accessor methods to the slots of objects of class Pca and its subclasses

● Data Source: CranContrib
● Keywords: methods, multivariate, robust
● Alias: getEigenvalues, getEigenvalues,methods, getLoadings, getLoadings-methods, getPrcomp, getPrcomp,methods, getQuan, getQuan,methods, getScale, getScale,methods, getScores, getScores,methods, getSdev, getSdev,methods
● 0 images

CovSde (Package: rrcov) : Stahel-Donoho Estimates of Multivariate Location and Scatter

Compute a robust estimate of location and scale using the Stahel-Donoho projection based estimator

● Data Source: CranContrib
● Keywords: multivariate, robust
● Alias: CovSde
● 0 images

CovMMest-class (Package: rrcov) : MM Estimates of Multivariate Location and Scatter

This class, derived from the virtual class "CovRobust" accomodates MM Estimates of multivariate location and scatter.

● Data Source: CranContrib
● Keywords: classes, multivariate, robust
● Alias: CovMMest-class
● 0 images

plot-methods (Package: rrcov) : Methods for Function 'plot' in Package 'rrcov'

Shows the Mahalanobis distances based on robust and/or classical estimates of the location and the covariance matrix in different plots. The following plots are available:

● Data Source: CranContrib
● Keywords: methods
● Alias: plot,CovClassic,missing-method, plot,CovClassic-method, plot,CovRobust,missing-method, plot,CovRobust-method, plot-methods
● 0 images

QdaCov (Package: rrcov) : Robust Quadratic Discriminant Analysis

Performs robust quadratic discriminant analysis and returns the results as an object of class QdaCov (aka constructor).

● Data Source: CranContrib
● Keywords: multivariate, robust
● Alias: QdaCov, QdaCov.default, QdaCov.formula
● 0 images

covMest (Package: rrcov) : Constrained M-Estimates of Location and Scatter

Computes constrained M-Estimates of multivariate location and scatter based on the translated biweight function (‘t-biweight’) using a High breakdown point initial estimate. The default initial estimate is the Minimum Volume Ellipsoid computed with CovMve. The raw (not reweighted) estimates are taken and the covariance matrix is standardized to determinant 1.

● Data Source: CranContrib
● Keywords: multivariate, robust
● Alias: covMest
● 0 images

CovSest-class (Package: rrcov) : S Estimates of Multivariate Location and Scatter

This class, derived from the virtual class "CovRobust" accomodates S Estimates of multivariate location and scatter computed by the ‘Fast S’ or ‘SURREAL’ algorithm.

● Data Source: CranContrib
● Keywords: classes, multivariate, robust
● Alias: CovSest-class
● 0 images

CovRobust (Package: rrcov) : Robust Location and Scatter Estimation

Computes a robust multivariate location and scatter estimate with a high breakdown point, using one of the available estimators.

● Data Source: CranContrib
● Keywords: multivariate, robust
● Alias: CovRobust
● 0 images

scorePlot-methods (Package: rrcov) :

Produces a score plot from an object (derived from) Pca-class.

● Data Source: CranContrib
● Keywords: hplot, multivariate
● Alias: scorePlot, scorePlot,ANY-method, scorePlot,Pca-method, scorePlot-methods
● 0 images