| bestPC | Choosing the best number of Principal Components (PCs) for lpda-pca model. |
| bestVariability | Choosing the best explained variability for lpda-pca model. |
| CVktest | CVktest evaluates the error rate classification with crossvalidation |
| CVloo | CVloo evaluates the error rate classification with leave one out procedure |
| lpda | Computing discriminating hyperplane for two groups |
| lpda.fit | lpda.fit computes the discriminating hyperplane for two groups |
| lpda.pca | lpda.pca computes a PCA to the original data and selects the desired PCs when Variability is supplied |
| lpdaCV | lpdaCV evaluates the error rate classification with a crossvalidation procedure |
| palmdates | Spectrometry and composition chemical of Spanish and Arabian palm dates |
| PCA | Principal Component Analysis |
| plot.lpda | Plot method for lpda classification |
| predict.lpda | Predict method for lpda classification |
| RNAseq | Simulated RNA-Seq dataset example |
| stand | stand center and scale a data matrix |
| stand2 | stand2 center and scale a data matrix with the parameters of another one |