Training DA Models Utilizing 'gips'
Find the Maximum A Posteriori Estimation
Extract probabilities for gipsmult object optimized with `return_pro...
Linear Discriminant Analysis with gips Covariance Projection
The constructor of a gipsmult class.
Quadratic Discriminant Analysis with multiple gips-projected covarianc...
Quadratic Discriminant Analysis with gips covariance projection
A log of a posteriori that the covariance matrix is invariant under pe...
Plot optimized matrix or optimization gipsmult object
Printing gipsmult object
Extends classical linear and quadratic discriminant analysis by incorporating permutation group symmetries into covariance matrix estimation. The package leverages methodology from the 'gips' framework to identify and impose permutation structures that act as a form of regularization, improving stability and interpretability in settings with symmetric or exchangeable features. Several discriminant analysis variants are provided, including pooled and class-specific covariance models, as well as multi-class extensions with shared or independent symmetry structures. For more details about 'gips' methodology see and Graczyk et al. (2022) <doi:10.1214/22-AOS2174> and Chojecki, Morgen, Kołodziejek (2025, <doi:10.18637/jss.v112.i07>).
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