R-based chemometric software
Download the R-based chemometric software developed by the Group of Chemometrics of the Italian Chemical Society.
- Istruzioni.txt (istruzioni in italiano)
- Instructions.txt (english instructions)
- Istruzioni.pdf (istruzioni in italiano)
- Instructions.pdf (english instructions)
- myscript.rar (November 5 2018)
- R-3.0.0.rar (October 22 2018)
- mylib.rar (September 17 2018)
- working.rar (January 23 2017)
- home.rar (January 10 2014)
- ggobi.rar (March 9 2013)
- pdf.rar (March 9 2013)
Note for the "old" users: with the updates dated April 6 2017 or following, the folder Perl.5.16 is no more required and can therefore be deleted
Matlab toolboxes for multivariate analysis
Collection of Matlab modules for calculating unsupervised and supervised mutlivariate models (download from the Milano Chemometrics and QSAR Research Group):
- Classification toolbox (for Matlab): classification (supervised pattern recognition) multivariate models: Discriminant Analysis, Partial Least Square Discriminant Analysis (PLSDA), Classification trees (CART), K-Nearest Neighbors (kNN), Potential Functions (Kernel Density Estimators), Support Vector Machines (SVM) and Soft Independent Modeling of Class Analogy (SIMCA).
- PCA toolbox (for Matlab): unsupervised multivariate models for data structure analysis: Principal Component Analysis (PCA), Multidimensional Scaling (MDS) and Cluster Analysis.
- N3-BNN toolbox (for Matlab): N3 (N-Nearest Neighbours), BNN (Binned Nearest Neighbours) and kNN (k Nearest Neighbours) local classification methods.
- Kohonen and CPANN toolbox (for Matlab): Kohonen Maps and Counterpropagation Artificial Neural networs (CPANNs), Supervised Kohonen networks and XY-fused networks.
PLS-Genetic Algorithm toolbox (for Matlab)
- PLS-GA toolbox (for Matlab): Matlab modules for variable selection based on Genetic Algorithms coupled with PLS by Riccardo Leardi (download from the Quality & Technology website, Department of Food Science, University of Copenhagen)
NSIMCA Toolbox for Multiway classification
The NSIMCA toolbox extends the SIMCA method to array of order >= 2. NSIMCA is written in MATLAB and includes few essential Guidelines. The toolbox is available from: www.models.life.ku.dk/nsimca.
The reference for the NSIMCA toolbox for MATLAB is: C. Durante, R. Bro, M. Cocchi, A classification tool for N-way array based on SIMCA methodology, Chemometrics & Intelligent Laboratory Systems. 106 (2011), 73-85.
Multi-way VIP for variable selection
The software calculates and displays VIP (Variable Influence in Projection) scores for NPLS and NPLSDA models. The Multi-way VIP code is written in MATLAB and can be downloaded at: www.models.life.ku.dk/nvip
It is described in: S. Favilla C. Durante,M. Li Vigni,M. Cocchi, Assessing feature relevance in NPLS models by VIP, Chemom. Intell. Lab. Syst. 2013 (129) 76-86.