= 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 ).