Ordination comprises several multivariate exploratory and explanatory techniques with theoretical foundations in geometric data analysis; see Podani (2000, ISBN:90-5782-067-6) for techniques and applications and Le Roux & Rouanet (2005) <doi:10.1007/1-4020-2236-0> for foundations. Greenacre (2010, ISBN:978-84-923846) shows how the most established of these, including principal components analysis, correspondence analysis, multidimensional scaling, factor analysis, and discriminant analysis, rely on eigen-decompositions or singular value decompositions of pre-processed numeric matrix data. These decompositions give rise to a set of shared coordinates along which the row and column elements can be measured. The overlay of their scatterplots on these axes, introduced by Gabriel (1971) <doi:10.1093/biomet/58.3.453>, is called a biplot. 'ordr' provides inspection, extraction, manipulation, and visualization tools for several popular ordination classes supported by a set of recovery methods. It is inspired by and designed to integrate into 'Tidyverse' workflows provided by Wickham et al (2019) <doi:10.21105/joss.01686>.
Version: 0.2.0 Depends: R (≥ 3.3.0), ggplot2 Imports: rlang, cli, MASS, stringr, tidyselect, scales, generics, magrittr, tibble, tidyr, dplyr, purrr, labeling, ggrepel, gggda Suggests: testthat, sessioninfo, gridExtra, mlpack, ddalpha, knitr, rmarkdown Published: 2025-07-10 DOI: 10.32614/CRAN.package.ordr Author: Jason Cory Brunson [aut, cre], Emily Paul [ctb], John Gracey [aut] Maintainer: Jason Cory Brunson <cornelioid at gmail.com> BugReports: https://github.com/corybrunson/ordr/issues License: GPL-3 URL: https://github.com/corybrunson/ordr, https://corybrunson.github.io/ordr/ NeedsCompilation: no Materials: README NEWS CRAN checks: ordr results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=ordr to link to this page.
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