Learning permutation symmetries with gips in R

07/03/2023

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by   Adam Chojecki, et al.

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The study of hidden structures in data presents challenges in modern statistics and machine learning. We introduce the 𝐠𝐢𝐩𝐬 package in R, which identifies permutation subgroup symmetries in Gaussian vectors. 𝐠𝐢𝐩𝐬 serves two main purposes: exploratory analysis in discovering hidden permutation symmetries and estimating the covariance matrix under permutation symmetry. It is competitive to canonical methods in dimensionality reduction while providing a new interpretation of the results. 𝐠𝐢𝐩𝐬 implements a novel Bayesian model selection procedure within Gaussian vectors invariant under the permutation subgroup introduced in Graczyk, Ishi, Kołodziejek, Massam, Annals of Statistics, 50 (3) (2022).