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rofanova: Robust Functional Analysis of Variance

Implements the robust functional analysis of variance (RoFANOVA), described in Centofanti et al. (2021) <doi:10.48550/arXiv.2112.10643>. It allows testing mean differences among groups of functional data by being robust against the presence of outliers.

Version: 1.0.0
Depends: fda.usc, robustbase
Imports: Rcpp, abind, parallel, stats
LinkingTo: Rcpp, RcppArmadillo
Suggests: knitr, rmarkdown, testthat
Published: 2022-01-21
DOI: 10.32614/CRAN.package.rofanova
Author: Fabio Centofanti [cre, aut], Bianca Maria Colosimo [aut], Marco Luigi Grasso [aut], Antonio Lepore [aut], Alessandra Menafoglio [aut], Biagio Palumbo [aut], Simone Vantini [aut]
Maintainer: Fabio Centofanti <fabio.centofanti at unina.it>
BugReports: https://github.com/unina-sfere/rofanova/issues
License: GPL-3
URL: https://github.com/unina-sfere/rofanova
NeedsCompilation: yes
SystemRequirements: GNU make
Materials: README NEWS
In views: FunctionalData
CRAN checks: rofanova results

Documentation:

Reference manual: rofanova.pdf

Downloads:

Package source: rofanova_1.0.0.tar.gz
Windows binaries: r-devel: rofanova_1.0.0.zip, r-release: rofanova_1.0.0.zip, r-oldrel: rofanova_1.0.0.zip
macOS binaries: r-release (arm64): rofanova_1.0.0.tgz, r-oldrel (arm64): rofanova_1.0.0.tgz, r-release (x86_64): rofanova_1.0.0.tgz, r-oldrel (x86_64): rofanova_1.0.0.tgz

Reverse dependencies:

Reverse imports: funcharts

Linking:

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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.