fdaoutlier: Outlier Detection Tools for Functional Data Analysis

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
Author:	Oluwasegun Taiwo Ojo [aut, cre, cph], Rosa Elvira Lillo [aut], Antonio Fernandez Anta [aut, fnd]
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

Documentation:

Reference manual:	fdaoutlier.pdf
Vignettes:	Simulation Models

Downloads:

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

Linking:

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