Generalized Principal Component Analysis R package genpca version 0.2.1 Generalized PCA and related matrix decompositions in weighted inner-product spaces. Methods are based on Allen, G. I., Grosenick, L., and Taylor, J. (2014) <doi:10.1080/01621459.2013.852978>, "A generalized least-square matrix decomposition", Journal of the American Statistical Association, 109(505), 145-159; and Abdi, H. (2007), "Singular value decomposition (SVD) and generalized singular value decomposition" <https://personal.utdallas.edu/~herve/Abdi-SVD2007-pretty.pdf>, in "Encyclopedia of Measurement and Statistics", 907-912. Software Depends: R (>= 4.1.0) Imports: Rcpp, eigencore (>= 1.0.3), FNN, Matrix, multivarious (>= 0.3.0), assertthat, methods, digest LinkingTo: Rcpp, RcppArmadillo, RcppEigen Suggests: testthat (>= 3.0.0), adjoin, irlba, matrixStats, clue, knitr, rmarkdown, ggplot2, albersdown, ragg, systemfonts Brad Buchsbaum <brad.buchsbaum@gmail.com> Comprehensive R Archive Network (CRAN) Brad Buchsbaum [aut, cre, cph] MIT + file LICENSE (https://CRAN.R-project.org/package=genpca/LICENSE) 2026-09-16 application/tgz https://CRAN.R-project.org/package=genpca doi:10.32614/CRAN.package.genpca en-US