Package: gipsDA 0.1.2

Norbert Maksymilian Frydrysiak

gipsDA: Training DA Models Utilizing 'gips'

Extends classical linear and quadratic discriminant analysis by incorporating permutation group symmetries into covariance matrix estimation. The package leverages methodology from the 'gips' framework to identify and impose permutation structures that act as a form of regularization, improving stability and interpretability in settings with symmetric or exchangeable features. Several discriminant analysis variants are provided, including pooled and class-specific covariance models, as well as multi-class extensions with shared or independent symmetry structures. For more details about 'gips' methodology see and Graczyk et al. (2022) <doi:10.1214/22-AOS2174> and Chojecki, Morgen, Kołodziejek (2025, <doi:10.18637/jss.v112.i07>).

Authors:Antoni Zbigniew Kingston [aut], Norbert Maksymilian Frydrysiak [aut, cre], Adam Przemysław Chojecki [ctb]

gipsDA_0.1.2.tar.gz
gipsDA_0.1.2.zip(r-4.7)gipsDA_0.1.2.zip(r-4.6)gipsDA_0.1.2.zip(r-4.5)
gipsDA_0.1.2.tgz(r-4.6-any)gipsDA_0.1.2.tgz(r-4.5-any)
gipsDA_0.1.2.tar.gz(r-4.7-any)gipsDA_0.1.2.tar.gz(r-4.6-any)
gipsDA_0.1.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
gipsDA/json (API)

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

Bug tracker:https://github.com/antonikingston/gipsda/issues

Pkgdown/docs site:https://antonikingston.github.io

On CRAN:

Conda:

3.88 score 504 downloads 8 exports 49 dependencies

Last updated from:82792dd568. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK186
source / vignettesOK205
linux-release-x86_64OK153
macos-release-arm64OK155
macos-oldrel-arm64OK168
windows-develOK95
windows-releaseOK122
windows-oldrelOK105
wasm-releaseOK124

Exports:find_MAPget_probabilities_from_gipsmultgipsldagipsmultgipsmultqdagipsqdalog_posteriori_of_gipsmultnew_gipsmult

Dependencies:abindclicpp11digestdisordRdplyrfarverfreealggenericsggplot2gipsgluegmpgtableisobandjsonlitelabelinglatticelifecyclemagicmagrittrMASSMatrixnumberspartitionspatchworkpermutationspillarpkgconfigpolynompurrrR6rbibutilsRColorBrewerRcppRdpackrlangS7scalessetsstringistringrtibbletidyrtidyselectutf8vctrsviridisLitewithr

Readme and manuals

Help Manual

Help pageTopics
Find the Maximum A Posteriori Estimationfind_MAP
Extract probabilities for 'gipsmult' object optimized with 'return_probabilities = TRUE'get_probabilities_from_gipsmult
Linear Discriminant Analysis with gips Covariance Projectioncoef.gipslda gipslda gipslda.data.frame gipslda.default gipslda.formula gipslda.matrix model.frame.gipslda pairs.gipslda plot.gipslda print.gipslda
The constructor of a 'gipsmult' class.gipsmult new_gipsmult
Quadratic Discriminant Analysis with multiple gips-projected covariancesgipsmultqda gipsmultqda.data.frame gipsmultqda.default gipsmultqda.formula gipsmultqda.matrix model.frame.gipsmultqda predict.gipsmultqda print.gipsmultqda
Quadratic Discriminant Analysis with gips covariance projectiongipsqda gipsqda.data.frame gipsqda.default gipsqda.formula gipsqda.matrix model.frame.gipsqda predict.gipsqda print.gipsqda
A log of a posteriori that the covariance matrix is invariant under permutationlog_posteriori_of_gipsmult
Plot optimized matrix or optimization 'gipsmult' objectplot.gipsmult
Printing 'gipsmult' objectprint.gipsmult