a gateway to R constructs would open up the capability of xlstat

While PCA is used to explore the relation between several quantitative variables, MCA (Multiple Correspondance Analysis) is used to explore the relation between several categorical variables. Some methods (PCAmix method for exemple) can deal with ...

Sensory and food industry.

Random Forests is a mainstream machine learning algorithm that is worth being implemented in XLSTAT. Maybe the XLSTAT decision trees code could be used as a baseline to develop Random Forests?

Is it very useful to have the possibility to apply MFA not only to continuous data (submitted to PCA) but also to frequency tables (e.g. CATA results, that should be submitted to CA). At the moment you are forced to use R to do that.

Currently the colors for groups are automatically chosen... if we could pick the colors ourselves it would be easier to track the same groups when you are doing lots of scatter plots

We generally do not know the number of classes in advance. Thus, we need to test for goodness of fit or we may just be looking at statistical noise. Please consider adding the cophenetic correlation coefficient (Sokal and Rohlf, 1962 or Farris) or...

This is an important and useful tool in testing the significance of multivariate statistics...it is used in environmental community analysis...e.g. comparing the abundance of species composition in two different localities. It is frequently used ...

Currently, XLSTAT DoE for Conjoint, CBC & Maxdiff generates the same questionaire to all respondents. It would be great to be able to generate different question sets to give to different respondent groups.