rrcovNA: Scalable Robust Estimators with High Breakdown Point for Incomplete Data

The package rrcovNA provides scalable robust estimators with high breakdown point for incomplete data (missing values) (Todorov et al. (2010) doi:10.1007/s11634-010-0075-2).

Installation

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

install.packages("rrcovNA")
library(rrcovNA)

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/rrcovNA", 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(rrcovNA)
#> Loading required package: rrcov
#> Loading required package: robustbase
#> Scalable Robust Estimators with High Breakdown Point (version 1.7-5)
#> Scalable Robust Estimators with High Breakdown Point for
#> Incomplete Data (version 0.5-0)
data(bush10)
mcd <- CovNAMcd(bush10)
mcd
#> 
#> Call:
#> CovNAMcd(x = bush10)
#> -> Method:  Minimum Covariance Determinant Estimator for incomplete data. 
#> 
#> Robust Estimate of Location: 
#>    V1     V2     V3     V4     V5  
#> 109.5  149.5  257.9  215.0  276.9  
#> 
#> Robust Estimate of Covariance: 
#>     V1       V2       V3       V4       V5     
#> V1    697.6    489.3  -3305.1   -671.4   -550.5
#> V2    489.3    424.5  -1889.0   -333.5   -289.5
#> V3  -3305.1  -1889.0  18930.9   4354.2   3456.4
#> V4   -671.4   -333.5   4354.2   1100.1    856.0
#> V5   -550.5   -289.5   3456.4    856.0    671.7
summary(mcd)
#> 
#> Call:
#> CovNAMcd(x = bush10)
#> 
#> Robust Estimate of Location: 
#>    V1     V2     V3     V4     V5  
#> 109.5  149.5  257.9  215.0  276.9  
#> 
#> Robust Estimate of Covariance: 
#>     V1       V2       V3       V4       V5     
#> V1    697.6    489.3  -3305.1   -671.4   -550.5
#> V2    489.3    424.5  -1889.0   -333.5   -289.5
#> V3  -3305.1  -1889.0  18930.9   4354.2   3456.4
#> V4   -671.4   -333.5   4354.2   1100.1    856.0
#> V5   -550.5   -289.5   3456.4    856.0    671.7
#> 
#> Eigenvalues of covariance matrix: 
#> [1]  21334.429    428.703     56.662      3.701      1.263
#> 
#> Robust Distances: 
#>  [1]    3.1071    1.1127    1.3864    1.1215    2.1500    3.0780  130.1256
#>  [8]  185.1492  200.1491   26.7795   63.9884    5.8178    2.8298    4.9464
#> [15]    2.1220    3.1128    1.0421    2.7172    2.9548    2.0638    1.4335
#> [22]    3.4786    0.1621    1.2949    1.0765    1.0287    2.5304    0.7860
#> [29]    3.4224    5.8211  151.4576  435.4440  238.2627   69.9555  323.5308
#> [36]  322.8153  312.4068  235.6941

plot(mcd)

plot(mcd, which="pairs")

plot(mcd, which="xydistance")

plot(mcd, which="xyqqchi2") 

## 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.