Decorrelation Projection Scalable to High Dimensional Data R package decorrelate version 0.1.6.4 Data whitening is a widely used preprocessing step to remove correlation structure since statistical models often assume independence. Here we use a probabilistic model of the observed data to apply a whitening transformation. This Gaussian Inverse Wishart Empirical Bayes model substantially reduces computational complexity, and regularizes the eigen-values of the sample covariance matrix to improve out-of-sample performance. Software Depends: R (>= 4.2.0), methods Imports: Rfast, irlba, graphics, Rcpp, CholWishart, Matrix, utils, stats LinkingTo: Rcpp, RcppArmadillo Suggests: knitr, pander, whitening, CCA, yacca, mvtnorm, ggplot2, cowplot, colorRamps, RUnit, latex2exp, clusterGeneration, rmarkdown Gabriel Hoffman <gabriel.hoffman@mssm.edu> Comprehensive R Archive Network (CRAN) Gabriel Hoffman [aut, cre] (ORCID: <https://orcid.org/0000-0002-0957-0224>) Artistic-2.0 2025-07-18 application/tgz https://CRAN.R-project.org/package=decorrelate doi:10.32614/CRAN.package.decorrelate