dimensio: Multivariate Data Analysis

Simple Principal Components Analysis (PCA) and Correspondence Analysis (CA) based on the Singular Value Decomposition (SVD). This package provides S4 classes and methods to compute, extract, summarize and visualize results of multivariate data analysis. It also includes methods for partial bootstrap validation described in Greenacre (1984) <isbn: 978-0-12-299050-2> and Lebart et al. (2006) <isbn: 978-2-10-049616-7>.

Version: 0.2.2
Depends: R (≥ 3.3)
Imports: ggplot2, methods, rlang
Suggests: covr, folio, FactoMineR, ggrepel, khroma, testthat (≥ 3.0.0), vdiffr (≥ 1.0.0)
Published: 2021-09-18
Author: Nicolas Frerebeau ORCID iD [aut, cre], Jean-Baptiste Fourvel ORCID iD [ctb], Brice Lebrun ORCID iD [ctb]
Maintainer: Nicolas Frerebeau <nicolas.frerebeau at u-bordeaux-montaigne.fr>
BugReports: https://github.com/tesselle/dimensio/issues
License: GPL (≥ 3)
URL: https://packages.tesselle.org/dimensio/, https://github.com/tesselle/dimensio
NeedsCompilation: no
Citation: dimensio citation info
Materials: README NEWS
CRAN checks: dimensio results


Reference manual: dimensio.pdf


Package source: dimensio_0.2.2.tar.gz
Windows binaries: r-devel: dimensio_0.2.2.zip, r-release: dimensio_0.2.2.zip, r-oldrel: dimensio_0.2.2.zip
macOS binaries: r-release (arm64): dimensio_0.2.2.tgz, r-release (x86_64): dimensio_0.2.2.tgz, r-oldrel: dimensio_0.2.2.tgz
Old sources: dimensio archive

Reverse dependencies:

Reverse imports: tabula


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