Changes in version 1.4.0 (2022-06-07)                  

    o   depends now R >= 3.5.0

    o   new data set pitprops14

    o   new function explainedVariation()

    o   reverted back to a single Cholesky whitening procedure (as Chol-cov and Chol-prec are really
	the same, just reversed ordering).  Default is now lower triangular loadings.

    o   whiteningCrossCov() depricated.  

    o   Instead whiteningLoadings() returns both loadings Phi and cross-correlation loadings Psi
	with the columns corresponding to the latent variables

    o   simOrtho() has positiveDiag option

    o   whiten() and other functions now label the latent variables (L1, L2, etc)

    o   whitening matrix and cross-cov matrix now also labelled (both rows and columns)

    o   whitening method used now attached as method attribute

                 Changes in version 1.3.0 (2021-11-07)                  

    o   update URLs

    o   new function simOrtho() to simulate random orthogonal matrices.

                 Changes in version 1.2.0 (2020-12-06)                  

    o   new whitening options "Chol.cov" and "Chol.prec" added.

    o   new function whiteningCrossCov() to compute the cross-covariance matrix
	for a given whitening transformation.

                 Changes in version 1.1.1 (2019-01-12)                  

    o   References to Kessy et al (2018) and Jendoubi and Strimmer (2019) updated.

    o   whiten() now has "center" option.

    o   New data set "forina1986" added (extended version of UCI wine data set)

                 Changes in version 1.1.0 (2018-07-14)                  

    o   The functions scca() and cca() now also compute the 
	loadings for X and Y.

    o   The data sets "lusc" and "nutrimouse" are now included.

    o   Updated nutrimouse data analysis script, and added R code
	for example analysis of lusc data. 

    o   Two functions loadplot() and corplot() have been added.

                 Changes in version 1.0.0 (2018-03-06)                  

    o   Public release on 3 March 2018.
	This package contains functions for computing whitening matrices, 
	for whitening data, and for (shrinkage) estimation of canonical 
	correlations and directions.