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]

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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 site:https://przechoj.github.io

On CRAN:

Conda:

covariance-estimationmachine-learningnormal-distribution

6.52 score 6 stars 31 scripts 599 downloads 16 exports 18 dependencies

Last updated 8 days agofrom:7b7841a64b. Checks:9 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 18 2025
R-4.5-winOKMar 18 2025
R-4.5-macOKMar 18 2025
R-4.5-linuxOKMar 18 2025
R-4.4-winOKMar 18 2025
R-4.4-macOKMar 18 2025
R-4.4-linuxOKMar 18 2025
R-4.3-winOKMar 18 2025
R-4.3-macOKMar 18 2025

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:abinddigestdisordRfreealggmplatticemagicmathjaxrMatrixnumberspartitionspermutationspolynomrbibutilsRcppRdpackrlangsets

A Gentle Introduction to Modeling with gips

Rendered fromgips.Rmdusingknitr::rmarkdownon Mar 18 2025.

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

Available Optimizers: How to Find Maximum A Posteriori?

Rendered fromOptimizers.Rmdusingknitr::rmarkdownon Mar 18 2025.

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

The Theory Behind gips

Rendered fromTheory.Rmdusingknitr::rmarkdownon Mar 18 2025.

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