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>.
|Author||Jason Cory Brunson [aut, cre] (<https://orcid.org/0000-0003-3126-9494>), Emily Paul [ctb]|
|Maintainer||Jason Cory Brunson <email@example.com>|
|Package repository||View on CRAN|
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