MEDA

The Multivariate Exploratory Data Analysis (MEDA) Toolbox in Matlab is a set of multivariate analysis tools for the exploration of data sets. There are several alternative tools in the market for that purpose, both commercial and free. The PLS_Toolbox from Eigenvector Inc. is a very nice example. The MEDA Toolbox is not intended to replace or being a competitor of any of these toolkits. Rather, the MEDA Toolbox is a complementary tool that includes several of our recent contributions to the field. Thus, traditional exploratory plots based on Principal Component Analysis (PCA) or Partial Least Squares (PLS), such as score, loading and residual plots, are combined with new methods: MEDA, oMEDA, SVI plots, ADICOV, EKF & CKF cross-validation, CSP, GPCA, ....

The MEDA Toolbox can be used to analyze normal size data sets (several hundreds of observations times several hundreds of variables) There is also an extension of the toolbox for large data sets, with millions of items, under folder Big Data.

The MEDA Toolbox is expected to work on Octave.