Package: BiGaRx 0.5.1

Kleber Garzón

BiGaRx: Unified Classical and Canonical Biplots

Classical and canonical biplots computed from a single singular value decomposition (SVD) engine. Includes the two biplots of Gabriel (1971) <doi:10.1093/biomet/58.3.453>: the GH-biplot, named after its row markers G and column markers H, which preserves the column metric (covariances and correlations between variables), and the JK-biplot, named after its row markers J and column markers K, which preserves the row metric (distances between individuals). Also includes the HJ-biplot of Galindo (1986) <https://upcommons.upc.edu/entities/publication/e17797dd-e20b-4fe5-b34a-f4cde41695ed>, which combines the row markers J and the column markers H so that rows and columns are both represented with maximum quality. Options include configurable preprocessing, supplementary rows and columns, quality of representation, contributions, goodness of fit, bootstrap confidence intervals following Nieto, Galindo, Leiva and Vicente-Galindo (2014) <doi:10.15446/rce.v37n2spe.47944>, and imputation of missing values by iterative low-rank approximation following Gabriel and Zamir (1979) <doi:10.1080/00401706.1979.10489819>. The canonical biplot, also known as the multivariate analysis of variance (MANOVA) biplot, follows Amaro, Vicente-Villardon and Galindo (2004) <https://www.redalyc.org/pdf/339/33908807.pdf>. It is available for one-way designs and for two-way designs with total, row, column and interaction biplots. It comes with multivariate tests, pairwise comparisons with Hotelling's T-squared statistic, log-ratio transformations for compositional data and confidence regions for the group means. The regions are circles or the ellipses of Krzanowski (1989) <doi:10.1093/biomet/76.1.107>, computed consistently in the scale of the within-groups covariance matrix. Plots use base graphics or 'ggplot2'.

Authors:Kleber Garzón [aut, cre], Roxana Barrezueta [aut]

BiGaRx_0.5.1.tar.gz
BiGaRx_0.5.1.zip(r-4.7-any)BiGaRx_0.5.1.zip(r-4.6-any)
BiGaRx_0.5.1.tar.gz(r-4.7-any)BiGaRx_0.5.1.tar.gz(r-4.6-any)
BiGaRx_0.5.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
BiGaRx/json (API)

# Install 'BiGaRx' in R:
install.packages('BiGaRx', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 14 exports 0 dependencies

Last updated from:4e67705224. Checks:6 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK106
source / vignettesOK209
linux-releaseOK123
windows-develOK68
windows-releaseOK75
wasm-releaseOK76

Exports:anova2_univariadaas_bigarxbigarxbigarx_bootbigarx_canonicalbigarx_manova2bigarx_tidycanonical_regionses_composicionalhotelling_paresimpute_svdinvertir_ejesmanova2_teststransformar_composicional

Dependencies:

Readme and manuals

Help Manual

Help pageTopics
Convierte un objeto 'prcomp' en un biplot de BiGaRxas_bigarx as_bigarx.prcomp
Gráfico de un biplot con 'ggplot2'autoplot.bigarx
Biplots clásicos GH, JK y HJ con un motor únicobigarx
Biplot con bootstrap: intervalos de confianzabigarx_boot
Biplot canónico (MANOVA biplot) de una víabigarx_canonical
MANOVA biplot de dos factoresanova2_univariada bigarx_manova2 manova2_tests
Datos ordenados de un biplotbigarx_tidy bigarx_tidy.bigarx_canonical bigarx_tidy.default tidy.bigarx
Regiones de confianza del biplot canónicocanonical_regions
Datos composicionaleses_composicional transformar_composicional
Comparaciones por pares con la T2 de Hotellinghotelling_pares
Imputa datos faltantes con una SVD de rango reducidoimpute_svd
Invertir el signo de ejes canonicosinvertir_ejes
Gráfico de un biplot con gráficos baseplot.bigarx
Gráficos de un biplot con bootstrapautoplot.bigarx_boot plot.bigarx_boot
Gráfico del biplot canónicoautoplot.bigarx_canonical plot.bigarx_canonical
Proyecta filas o columnas suplementariaspredict.bigarx predict.bigarx_canonical
Resumen de un biplot con bootstrapsummary.bigarx_boot
Resumen de un biplotsummary.bigarx summary.bigarx_canonical