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gips
View on CRAN: Click
here
Download and install gips package within the R console
Install from CRAN:
install.packages("gips")
Install from Github:
library("remotes")
install_github("cran/gips") Install by package version:
library("remotes")
install_version("gips", "1.2.3") Attach the package and use:
library("gips")
Maintained by
Adam Przemysław Chojecki
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-10-13
Latest Update: 2025-03-18
Description:
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)
.
How to cite:
Adam Przemysław Chojecki (2022). gips: Gaussian Model Invariant by Permutation Symmetry. R package version 1.2.3, https://cran.r-project.org/web/packages/gips. Accessed 04 Jun. 2026.
Previous versions and publish date:
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imports, suggests or enhances
Complete documentation for gips
Functions, R codes and Examples using
the gips R package
Some associated functions: AIC.gips . as.character.gips . as.character.gips_perm . calculate_gamma_function . compare_posteriories_of_perms . find_MAP . forget_perms . get_probabilities_from_gips . get_structure_constants . gips . gips_perm . logLik.gips . log_posteriori_of_gips . plot.gips . prepare_orthogonal_matrix . print.gips . print.gips_perm . project_matrix . summary.gips .
Some associated R codes: calculate_gamma_function.R . estimate_probabilities.R . find_MAP.R . get_structure_constants.R . gips_class.R . gips_perm_class.R . log_posteriori_of_gips.R . prepare_orthogonal_matrix.R . project_matrix.R . utils.R . Full gips package functions and examples
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