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rrcov: Scalable Robust Estimators with High Breakdown Point

The package rrcov provides scalable robust estimators with high breakdown point and covers a large number of robustified multivariate analysis methods, starting with robust estimators for the multivariate location and covariance matrix (MCD, MVE, S, MM, SD), the deterministic versions of MCD, S and MM estimates and regularized versions (MRCD) for high dimensions. These estimators are used to conduct robust principal components analysis (PcaCov()), linear and quadratic discriminant analysis (Linda(), Qda()), MANOVA. Projection pursuit algorithms for PCA to be applied in high dimensions are also available (PcaHubert(), PcaGrid() and PcaProj()).

Installation

The rrcov package is on CRAN (The Comprehensive R Archive Network) and the latest release can be easily installed using the command

install.packages("rrcov")
library(rrcov)

Building from source

To install the latest stable development version from GitHub, you can pull this repository and install it using

## install.packages("remotes")
remotes::install_github("valentint/rrcov", build_opts = c("--no-build-vignettes"))

Of course, if you have already installed remotes, you can skip the first line (I have commented it out).

Example

This is a basic example which shows you if the package is properly installed:


library(rrcov)
#> Loading required package: robustbase
#> Scalable Robust Estimators with High Breakdown Point (version 1.7-3)
data(hbk)
(out <- CovMcd(hbk))
#> 
#> Call:
#> CovMcd(x = hbk)
#> -> Method:  Fast MCD(alpha=0.5 ==> h=40); nsamp = 500; (n,k)mini = (300,5) 
#> 
#> Robust Estimate of Location: 
#>       X1        X2        X3         Y  
#>  1.55833   1.80333   1.66000  -0.08667  
#> 
#> Robust Estimate of Covariance: 
#>     X1        X2        X3        Y       
#> X1   1.58739   0.03129   0.21694   0.10748
#> X2   0.03129   1.60733   0.25612   0.02864
#> X3   0.21694   0.25612   1.47254  -0.18174
#> Y    0.10748   0.02864  -0.18174   0.44081

Community guidelines

Report issues and request features

If you experience any bugs or issues or if you have any suggestions for additional features, please submit an issue via the Issues tab of this repository. Please have a look at existing issues first to see if your problem or feature request has already been discussed.

Contribute to the package

If you want to contribute to the package, you can fork this repository and create a pull request after implementing the desired functionality.

Ask for help

If you need help using the package, or if you are interested in collaborations related to this project, please get in touch with the package maintainer.

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Version

Install

install.packages('rrcov')

Monthly Downloads

29,998

Version

1.7-5

License

GPL (>= 3)

Issues

1

Pull Requests

0

Stars

2

Forks

1

Maintainer

Valentin Todorov

Last Published

January 30th, 2024

Functions in rrcov (1.7-5)

CovControlOgk

Constructor function for objects of class "CovControlOgk"
CovControlMcd

Constructor function for objects of class "CovControlMcd"
CovControlMest-class

Class 'CovControlMest' - contains control parameters for "CovMest"
CovControlMrcd

Constructor function for objects of class "CovControlMrcd"
CovControlMve

Constructor function for objects of class "CovControlMve"
CovControlOgk-class

Class 'CovControlOgk' - contains control parameters for CovOgk
CovControlMrcd-class

Class 'CovControlMrcd' - contains control parameters for CovMrcd()
CovControlSde-class

Class 'CovControlSde' - contains control parameters for "CovSde"
CovControlMest

Constructor function for objects of class "CovControlMest"
CovControlMve-class

Class 'CovControlMve' - contains control parameters for CovMve
CovControlSest

Constructor function for objects of class "CovControlSest"
CovMMest

MM Estimates of Multivariate Location and Scatter
CovMMest-class

MM Estimates of Multivariate Location and Scatter
CovControlSde

Constructor function for objects of class "CovControlSde"
CovMcd

Robust Location and Scatter Estimation via MCD
CovMest-class

Constrained M-estimates of Multivariate Location and Scatter
CovMcd-class

MCD Estimates of Multivariate Location and Scatter
CovMest

Constrained M-Estimates of Location and Scatter
CovMrcd-class

MRCD Estimates of Multivariate Location and Scatter
CovControlSest-class

Class 'CovControlSest' - contains control parameters for "CovSest"
CovSde-class

Stahel-Donoho Estimates of Multivariate Location and Scatter
CovRobust

Robust Location and Scatter Estimation
CovOgk

Robust Location and Scatter Estimation - Ortogonalized Gnanadesikan-Kettenring (OGK)
CovSde

Stahel-Donoho Estimates of Multivariate Location and Scatter
CovMrcd

Robust Location and Scatter Estimation via Minimum Regularized Covariance Determonant (MRCD)
CovMve

Robust Location and Scatter Estimation via MVE
CovMve-class

MVE Estimates of Multivariate Location and Scatter
CovOgk-class

OGK Estimates of Multivariate Location and Scatter
CovRobust-class

Class "CovRobust" - virtual base class for robust estimates of multivariate location and scatter
LdaClassic-class

Class "LdaClassic" - Linear Discriminant Analysis
LdaRobust-class

Class "LdaRobust" is a virtual base class for all robust LDA classes
CovSest

S Estimates of Multivariate Location and Scatter
LdaPP-class

Class "LdaPP" - Robust method for Linear Discriminant Analysis by Projection-pursuit
Lda-class

Class "Lda" - virtual base class for all classic and robust LDA classes
Linda-class

Class "Linda" - Robust method for LINear Discriminant Analysis
PcaGrid

Robust Principal Components based on Projection Pursuit (PP): GRID search Algorithm
LdaClassic

Linear Discriminant Analysis
PcaHubert

ROBPCA - ROBust method for Principal Components Analysis
PcaHubert-class

Class "PcaHubert" - ROBust method for Principal Components Analysis
LdaPP

Robust Linear Discriminant Analysis by Projection Pursuit
PcaLocantore

Spherical Principal Components
PcaClassic

Principal Components Analysis
CovSest-class

S Estimates of Multivariate Location and Scatter
Linda

Robust Linear Discriminant Analysis
OsloTransect

Oslo Transect Data
SummaryLda-class

Class "SummaryLda" - summary of "Lda" objects
SummaryPca-class

Class "SummaryPca" - summary of "Pca" objects
PcaCov-class

Class "PcaCov" - Robust PCA based on a robust covariance matrix
QdaClassic

Quadratic Discriminant Analysis
PcaCov

Robust PCA based on a robust covariance matrix
PcaProj-class

Class "PcaProj" - Robust PCA using PP - Croux and Ruiz-Gazen (2005) algorithm
covMest

Constrained M-Estimates of Location and Scatter
PcaGrid-class

Class "PcaGrid" - Robust PCA using PP - GRID search Algorithm
Pca-class

Class "Pca" - virtual base class for all classic and robust PCA classes
PcaProj

Robust Principal Components based on Projection Pursuit (PP): Croux and Ruiz-Gazen (2005) algorithm
QdaCov-class

Class "QdaCov" - Robust methods for Quadratic Discriminant Analysis
SummaryQda-class

Class "SummaryQda" - summary of "Qda" objects
T2.test

Robust Hotelling T2 test
bus

Automatic vehicle recognition data
diabetes

Reaven and Miller diabetes data
PcaLocantore-class

Class "PcaLocantore" Spherical Principal Components
PcaRobust-class

Class "PcaRobust" is a virtual base class for all robust PCA classes
maryo

Marona and Yohai Artificial Data
bushmiss

Campbell Bushfire Data with added missing data items
QdaCov

Robust Quadratic Discriminant Analysis
PcaClassic-class

Class "PcaClassic" - Principal Components Analysis
isSingular-methods

Check if a covariance matrix (object of class 'Cov') is singular
PredictLda-class

Class "PredictLda" - prediction of "Lda" objects
Wilks.test

Classical and Robust One-way MANOVA: Wilks Lambda
lmom32

Hosking and Wallis Data Set, Table 3.2
QdaRobust-class

Class "QdaRobust" is a virtual base class for all robust QDA classes
un86

United Nations Data - 1986
wages

Wages and Hours
getEllipse

Calculates the points for drawing a confidence ellipsoid
octane

Octane data
PredictQda-class

Class "PredictQda" - prediction of "Qda" objects
getLoadings-methods

Accessor methods to the essential slots of Pca and its subclasses
SummaryCov-class

Class "SummaryCov" - summary of "Cov" objects
SummaryCovRobust-class

Class "SummaryCovRobust" - summary of "CovRobust" objects
fruit

Fruit data set
hemophilia

Hemophilia Data
biplot-methods

Biplot for Principal Components (objects of class 'Pca')
getCenter-methods

Accessor methods to the essential slots of Cov and its subclasses
Qda-class

Class "Qda" - virtual base class for all classic and robust QDA classes
lmom33

Hosking and Wallis Data Set, Table 3.3
restimate-methods

Methods for Function estimate in Package 'rrcov'
QdaClassic-class

Class "QdaClassic" - Quadratic Discriminant Analysis
machines

Computer Hardware
fish

Fish Catch Data Set
pca.scoreplot

Score plot for Principal Components (objects of class 'Pca')
rrcov-utils

Different utility functions to be used in rrcov and packages depending on rrcov
salmon

Salmon data
olitos

Olive Oil Data
ionosphere

Johns Hopkins University Ionosphere database.
pottery

Archaic Greek Pottery data
rice

Rice taste data
wolves

Skull dimensions of the wolf Canis lupus L.
pca.distances

Compute score and orthogonal distances for Principal Components (objects of class 'Pca')
scorePlot-methods

Score plot for Principal Components (objects of class 'Pca')
soil

Exchangable cations in forest soil data set
plot-methods

Methods for Function 'plot' in Package 'rrcov'
Cov-class

Class "Cov" -- a base class for estimates of multivariate location and scatter
Cascades

Annual precipitation totals for the North Cascades region
CovControl-class

Class "CovControl" is a VIRTUAL base control class
CovClassic

Classical Estimates of Multivariate Location and Scatter
CovClassic-class

Class "CovClassic" - classical estimates of multivariate location and scatter
Appalachia

Annual maximum streamflow in central Appalachia
CovControlMMest

Constructor function for objects of class "CovControlMMest"
CovControlMMest-class

Class 'CovControlMMest' - contains control parameters for "CovMMest"
CovControlMcd-class

Class 'CovControlMcd' - contains control parameters for CovMcd
Cars

Consumer reports car data: dimensions