= Features =

● Powerful multivariate analysis methods and design of           experiment.

● Easy data importing options with intuitive workflows              and interface.

● Outstanding graphics, plots and interactive data                     visualization tools.

= Explorative Methods =

● PCA ( Principal Component Analysis )

● MCR ( Multivariate Curve Resolution )

= Regression Methods =

● MLR (Multiple Linear Regression )

● PCR ( Principal Component Regression )

● PLSR ( Partial Least Squares Regression )

● SVR ( Support Vector Machines Regression )

● L-PLS Regression, incorporating three data tables.

= Classification Methods =

● Projection using PCA, PCR or PLSR models.

● SIMCA ( Soft Independent Modelling of Class Analogy )

● LDA ( Linear Discriminant Analysis ) with Linear,                        Quadratic, Mahalonobis options.

● PCA-LDA, for classification of correlated data by LDA.

● SVC ( Support Vector Machines Classification ).