What is new


  • Added section about normalization to Preprocessing chapter.
  • Added section about missing values replacement to Preprocessing chapter.
  • Improved description of validation procedure in PCA, PLS and other methods, including the use of Procrustes cross-validation.
  • Small improvements in selected parts of text.


Improved description of iPLS section, including new features appeared in v. 0.13.1.


  • Added section explaining how to use pcv.nareplace() method

  • Added separate section for Procrustes cross-validation.


Added description of new features appeared in v. 0.13.0 of the package, including new plotting method plotRMSERatio() for PLS models and new cross-validation possibilities. Validation of PLS model text has been extended and made as separate section.


Added description of new features appeared in v. 0.12.0 of the package, including:

  • new preprocessing methods prep.transform(), prep.varsel().
  • improvements to prep.savgol() and prep.norm().
  • a possibility to combine several preprocessing method together and apply at once.

In addition to that, text for Datasets chapter has been revised to provide more clear guides while the part about preprocessing was detached and now is available as separate chapter where you can find all details. Description of ALS baseline correction was moved to the section Correction of baseline.


Added description of new features added in v. 0.11.4:

  • using test set validation in iPLS.
  • possibility to force selected contribution and spectral values in MCR-ALS.
  • added information about how to provide user defined indices for pure variables in Purity method
  • added link to relevant paper in the PCA model complexity section



  • section about MCR Purity method has been re-written to correspond to the algorithm changes in v. 0.11.1.


  • added chapters about MCR methods implemented in v. 0.11.0.
  • added description of new preprocessing methods prep.alsbasecorr()
  • several small improvements in text