| ICSOutlier-package {ICSOutlier} | R Documentation |
Outlier Detection Using Invariant Coordinate Selection
Description
Multivariate outlier detection is performed using invariant coordinates where the package offers different methods to choose the appropriate components. ICS is a general multivariate technique with many applications in multivariate analysis. ICSOutlier offers a selection of functions for automated detection of outliers in the data based on a fitted ICS object or by specifying the dataset and the scatters of interest. The current implementation targets data sets with only a small percentage of outliers.
Details
The DESCRIPTION file:
| Package: | ICSOutlier |
| Type: | Package |
| Title: | Outlier Detection Using Invariant Coordinate Selection |
| Version: | 0.4-0 |
| Date: | 2023-12-13 |
| Authors@R: | c(person("Klaus", "Nordhausen", email = "klausnordhausenR@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-3758-8501")), person("Aurore", "Archimbaud", email = "aurore.archimbaud@live.fr", role = "aut", comment = c(ORCID = "0000-0002-6511-9091")), person("Anne", "Ruiz-Gazen", email = "anne.ruiz-gazen@tse-fr.eu", role = "aut", comment = c(ORCID = "0000-0001-8970-8061"))) |
| Author: | Klaus Nordhausen [aut, cre] (<https://orcid.org/0000-0002-3758-8501>), Aurore Archimbaud [aut] (<https://orcid.org/0000-0002-6511-9091>), Anne Ruiz-Gazen [aut] (<https://orcid.org/0000-0001-8970-8061>) |
| Maintainer: | Klaus Nordhausen <klausnordhausenR@gmail.com> |
| Depends: | R (>= 3.0.0), methods, ICS (>= 1.4-0), moments |
| Imports: | graphics, grDevices, mvtnorm, parallel |
| Suggests: | ICSClust, REPPlab, testthat (>= 3.0.0) |
| Description: | Multivariate outlier detection is performed using invariant coordinates where the package offers different methods to choose the appropriate components. ICS is a general multivariate technique with many applications in multivariate analysis. ICSOutlier offers a selection of functions for automated detection of outliers in the data based on a fitted ICS object or by specifying the dataset and the scatters of interest. The current implementation targets data sets with only a small percentage of outliers. |
| License: | GPL (>= 2) |
| NeedsCompilation: | no |
| Packaged: | 2023-09-18 08:47:44 UTC; admin |
| Repository: | CRAN |
| Date/Publication: | 2023-09-18 09:30:08 UTC |
| Config/testthat/edition: | 3 |
| RoxygenNote: | 7.2.3 |
| Roxygen: | list(markdown = TRUE) |
| Encoding: | UTF-8 |
Index of help topics:
HTP Production Measurements of High-Tech Parts -
Full Rank Case
HTP2 Production Measurements of High-Tech Parts -
Singular Case
HTP3 Production Measurements of High-Tech Parts -
Nearly Singular Case
ICSOutlier-package Outlier Detection Using Invariant Coordinate
Selection
ICS_outlier Outlier Detection Using ICS
comp.norm.test Selection of Nonnormal Invariant Components
Using Marginal Normality Tests
comp.simu.test Selection of Nonnormal Invariant Components
Using Simulations
comp_norm_test Selection of Nonnormal Invariant Components
Using Marginal Normality Tests
comp_simu_test Selection of Nonnormal Invariant Components
Using Simulations
dist.simu.test Cut-Off Values Using Simulations for the
Detection of Extreme ICS Distances
dist_simu_test Cut-Off Values Using Simulations for the
Detection of Extreme ICS Distances
ics.distances Squared ICS Distances for Invariant Coordinates
ics.outlier Outlier Detection Using ICS
icsOut-class Class icsOut
ics_distances Squared ICS Distances for Invariant Coordinates
plot.ICS_Out Distances Plot for an 'ICS_Out' Object
plot.icsOut Distances Plot for an icsOut Object
print.ICS_Out Vector of Outlier Indicators
print.icsOut Vector of Outlier Indicators
summary.ICS_Out Summary of an 'ICS_Out' Object Summarizes an
'ICS_Out' object in an informative way.
summary.icsOut Summarize a icsOut object
Author(s)
Klaus Nordhausen [aut, cre] (<https://orcid.org/0000-0002-3758-8501>), Aurore Archimbaud [aut] (<https://orcid.org/0000-0002-6511-9091>), Anne Ruiz-Gazen [aut] (<https://orcid.org/0000-0001-8970-8061>)
Maintainer: Klaus Nordhausen <klausnordhausenR@gmail.com>
References
Archimbaud, A., Nordhausen, K. and Ruiz-Gazen, A. (2018), ICS for multivariate outlier detection with application to quality control. Computational Statistics & Data Analysis, 128:184-199. ISSN 0167-9473. doi:10.1016/j.csda.2018.06.011.
Archimbaud, A., Nordhausen, K. and Ruiz-Gazen, A. (2018), ICSOutlier: Unsupervised Outlier Detection for Low-Dimensional Contamination Structure. The R Journal, 10:234-250. doi:10.32614/RJ-2018-034.