Package: gips 1.2.3.9000

Adam Przemysław Chojecki

gips: Gaussian Model Invariant by Permutation Symmetry

Find the permutation symmetry group such that the covariance matrix of the given data is approximately invariant under it. Discovering such a permutation decreases the number of observations needed to fit a Gaussian model, which is of great use when it is smaller than the number of variables. Even if that is not the case, the covariance matrix found with 'gips' approximates the actual covariance with less statistical error. The methods implemented in this package are described in Graczyk et al. (2022) <doi:10.1214/22-AOS2174>. Documentation about 'gips' is provided via its website at <https://przechoj.github.io/gips/> and the paper by Chojecki, Morgen, Kołodziejek (2025, <doi:10.18637/jss.v112.i07>).

Authors:Adam Przemysław Chojecki [aut, cre], Paweł Morgen [aut], Bartosz Kołodziejek [aut]

gips_1.2.3.9000.tar.gz
gips_1.2.3.9000.zip(r-4.7)gips_1.2.3.9000.zip(r-4.6)gips_1.2.3.9000.zip(r-4.5)
gips_1.2.3.9000.tgz(r-4.6-any)gips_1.2.3.9000.tgz(r-4.5-any)
gips_1.2.3.9000.tar.gz(r-4.7-any)gips_1.2.3.9000.tar.gz(r-4.6-any)
gips_1.2.3.9000.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
gips/json (API)
NEWS

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

Bug tracker:https://github.com/przechoj/gips/issues

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

On CRAN:

Conda:

covariance-estimationmachine-learningnormal-distribution

6.52 score 9 stars 1 packages 27 scripts 750 downloads 16 exports 17 dependencies

Last updated from:f8e955c918. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK149
source / vignettesOK274
linux-release-x86_64OK154
macos-release-arm64OK96
macos-oldrel-arm64OK76
windows-develOK107
windows-releaseOK88
windows-oldrelOK94
wasm-releaseOK131

Exports:calculate_gamma_functioncompare_log_posteriories_of_permscompare_posteriories_of_permsfind_MAPforget_permsget_probabilities_from_gipsget_structure_constantsgipsgips_permlog_posteriori_of_gipsnew_gipsnew_gips_permprepare_orthogonal_matrixproject_matrixvalidate_gipsvalidate_gips_perm

Dependencies:abinddigestdisordRfreealggmplatticemagicMatrixnumberspartitionspermutationspolynomrbibutilsRcppRdpackrlangsets

A Gentle Introduction to Modeling with gips

Rendered fromgips.Rmdusingknitr::rmarkdownon May 23 2026.

Last update: 2025-03-17
Started: 2022-09-14

Available Optimizers: How to Find Maximum A Posteriori?

Rendered fromOptimizers.Rmdusingknitr::rmarkdownon May 23 2026.

Last update: 2025-03-17
Started: 2022-09-06

The Theory Behind gips

Rendered fromTheory.Rmdusingknitr::rmarkdownon May 23 2026.

Last update: 2025-03-17
Started: 2022-09-13