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A collection of functions for outlier detection in functional data analysis. Methods implemented include directional outlyingness by Dai and Genton (2019) <doi:10.1016/j.csda.2018.03.017>, MS-plot by Dai and Genton (2018) <doi:10.1080/10618600.2018.1473781>, total variation depth and modified shape similarity index by Huang and Sun (2019) <doi:10.1080/00401706.2019.1574241>, and sequential transformations by Dai et al. (2020) <doi:10.1016/j.csda.2020.106960 among others. Additional outlier detection tools and depths for functional data like functional boxplot, (modified) band depth etc., are also available.
Version: | 0.2.1 |
Depends: | R (≥ 2.10) |
Imports: | MASS |
Suggests: | testthat (≥ 2.1.0), covr, spelling, knitr, rmarkdown |
Published: | 2023-09-30 |
DOI: | 10.32614/CRAN.package.fdaoutlier |
Author: | Oluwasegun Taiwo Ojo
|
Maintainer: | Oluwasegun Taiwo Ojo <seguntaiwoojo at gmail.com> |
BugReports: | https://github.com/otsegun/fdaoutlier/issues |
License: | GPL-3 |
URL: | https://github.com/otsegun/fdaoutlier |
NeedsCompilation: | yes |
Language: | en-US |
Materials: | README NEWS |
In views: | FunctionalData |
CRAN checks: | fdaoutlier results |
Reference manual: | fdaoutlier.pdf |
Vignettes: |
Simulation Models |
Package source: | fdaoutlier_0.2.1.tar.gz |
Windows binaries: | r-devel: fdaoutlier_0.2.1.zip, r-release: fdaoutlier_0.2.1.zip, r-oldrel: fdaoutlier_0.2.1.zip |
macOS binaries: | r-release (arm64): fdaoutlier_0.2.1.tgz, r-oldrel (arm64): fdaoutlier_0.2.1.tgz, r-release (x86_64): fdaoutlier_0.2.1.tgz, r-oldrel (x86_64): fdaoutlier_0.2.1.tgz |
Old sources: | fdaoutlier archive |
Please use the canonical form https://CRAN.R-project.org/package=fdaoutlier to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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