Linear Programming Discriminant Analysis

---

Documentation for package ‘lpda’ version 1.0.1

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

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