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Changelog

Source: NEWS.md

genpca 0.1.0

  • Initial CRAN submission.
  • Generalized PCA with row metric M and column metric A (genpca()), following Allen, Grosenick & Taylor (2014).
  • Covariance-based GPCA from a precomputed C = X' M X (genpca_cov()), with eigen and gmd paths.
  • Multiple computational backends: eigen, spectra (matrix-free C++ via RSpectra), randomized, and deflation. The auto heuristic picks among them.
  • Generalized PLS / PLS-SVD on two blocks (genpls(), genplsc()) and an operator-level interface (gplssvd_op()) that avoids materialising whitened matrices.
  • Sparse functional PCA (sfpca()), regularised PLS (rpls()), and matrix-normal PCA via maximum residual likelihood (mnpca_mrl()).
  • Maximum-likelihood metric learning (gpca_mle()).
  • SPD constraint handling with "ridge", "clip", and "identity" remediation strategies.
  • Vignettes covering getting started, metric recipes, scaling, and a reference implementation for GPLSSVD.