Forum – Page 10

Updating PCA & nipals

plsda and splsda have been further improved so that all the S3 functions predict, print, plotIndiv, plot3dIndiv can be used with these new classes
Several prediction methods are now available to predict the classes of test data with plsda andsplsda, see argument 'method' (max.dist, class.dist, centroids.dist, mahalanobis.dist) in thepredict function

plsda and splsda functions are implemented to perform PLS Discriminant Analysis (PLS-DA) and sparse PLS-DA respectively
breast.tumors data set is introduced to illustrate the (s)PLS-DA
PCA can also been performed with missing values using the NIPALS algorithm and 3D plots are also available for PCA
Network (updated) to display relevant associations between variables for (r)CCA and (s)PLS, with a new similarity function
A new similarity measure has been included in cim function and the arguments hclusfuncand distfunc to display Clustered image maps (heatmaps)