Linear Programming Discriminant Analysis
Choosing the best number of Principal Components (PCs) for lpda-pca mo...
Choosing the best explained variability for lpda-pca model.
CVktest evaluates the error rate classification with crossvalidation
CVloo evaluates the error rate classification with leave one out proce...
lpda.fit computes the discriminating hyperplane for two groups
lpda.pca computes a PCA to the original data and selects the desired P...
Computing discriminating hyperplane for two groups
lpdaCV evaluates the error rate classification with a crossvalidation ...
Principal Component Analysis
Plot method for lpda classification
Predict method for lpda classification
stand center and scale a data matrix
stand2 center and scale a data matrix with the parameters of another o...
Classification method obtained through linear programming. It is advantageous with respect to the classical developments when the distribution of the variables involved is unknown or when the number of variables is much greater than the number of individuals. LPDA method is published in Nueda, et al. (2022) "LPDA: A new classification method based on linear programming". <doi:10.1371/journal.pone.0270403>.