HDoutliers

Package: HDoutliers
Version: 0.2
Date: 2016-06-22
Title: Leland Wilkinson's Algorithm for Detecting Multidimensional
Outliers
Authors@R: c(person("Leland", "Wilkinson", role = c("aut"),
email = "leland.wilkinson@gmail.com"),
person("Chris", "Fraley", role = c("cre"), email = "cfraley@tableau.com"))
Author: Leland Wilkinson [aut], Chris Fraley [cre]
Maintainer: Chris Fraley <cfraley@tableau.com>
Depends: R (>= 3.1.0), FNN, FactoMineR
Description: An implementation of an algorithm for outlier detection that can handle a) data with a mixed categorical and continuous variables, b) many columns of data, c) many rows of data, d) outliers that mask other outliers, and e) both unidimensional and multidimensional datasets. Unlike ad hoc methods found in many machine learning papers, HDoutliers is based on a distributional model that uses probabilities to determine outliers.
License: GPL (>= 2)
URL: https://www.r-project.org
NeedsCompilation: no
Packaged: 2016-06-22 22:46:06 UTC; cfraley
Repository: CRAN
Date/Publication: 2016-06-23 01:24:55

Install log

* installing to library '/home/ddbj/local/lib64/R/library'
* installing *source* package 'HDoutliers' ...
** package 'HDoutliers' successfully unpacked and MD5 sums checked
** R
** data
** preparing package for lazy loading
** help
*** installing help indices
  converting help for package 'HDoutliers'
    finding HTML links ... done
    HDoutliers                              html  
    dots                                    html  
    ex2D                                    html  
    getHDmembers                            html  
    getHDoutliers                           html  
    plotHDoutliers                          html  
** building package indices
** installing vignettes
** testing if installed package can be loaded
* DONE (HDoutliers)
Making 'packages.html' ... done