Gaussian Model Invariant by Permutation Symmetry
Akaike's An Information Criterion for gips class
Transform the gips_perm object to a character vector
Transform the gips object to a character vector
Calculate Gamma function
Compare the posteriori probabilities of 2 permutations
Find the Maximum A Posteriori Estimation
Forget the permutations for gips object optimized with `save_all_per...
Extract probabilities for gips object optimized with `return_probabi...
Get Structure Constants
Permutation object
The constructor of a gips class.
A log of a posteriori that the covariance matrix is invariant under pe...
Extract the Log-Likelihood for gips class
Plot optimized matrix or optimization gips object
Prepare orthogonal matrix
Printing gips_perm object
Printing gips object
Project matrix after optimization
Summarizing the gips object
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>).
Useful links