Version 2007.6 of XLSTAT is available and brings the following new features:
- Canonical correlation analysis has been added to the ADA module.
- The GPA function, available in both the MX and ADA is now more flexible as you can now easily select configurations that do not have the same number of dimensions. This is very useful in sensory data analysis.
- The GPA algorithm has been upgraded. It is significantly quicker and offers a new alternative approach for missing data : if a missing data is met for a given triplet object/configuration/dimension, the data are considered as missing for the couple object/configuration. Then, it is not necessary to consider the couple configuration/dimension or the whole object as being missing. This option has advantages that should be discribed soon in an article.
- The PLSPM module has been improved.
This short course delivered online will show consumer scientists how to use partial least squares in XLSTAT for relating consumer acceptability to sensory/analytic measures.
This short course delivered online will show consumer scientists how to set up and learn about the routines available in XLSTAT for relating consumer acceptability to sensory/analytic measures.
This webinar presents the principles of Supervised Machine Learning & Prediction, with demos using the XLSTAT data analysis software. May 5, 2020 5:00 PM - 6:00 PM CEST