Among the mathematical tools, Xlstat proposes matrix calculations: sums and products of matrixes. Nevertheless it does not propose matrix diagonalization, which would be useful to study the matrixes of changes of states in time, and tpo enrich t...

Introduction of kernel functions in PLS can significantly improve the explanatory power of regression. Hope it comes true in future.

Right now XLstat offers only an annual subscription. I have the need to use XLstat and prefer not to use other software, but with a single, small project cannot justify $1395 for a couple days worth of analyses. I'd gladly pay for a month's subscr...

MARS is very good for modeling where the variables have a change in importance across a data set. fx=f(x) if a> some # and 0 otherwisesee https://en.wikipedia.org/wiki/Kriging#:~:text=From%20Wikipedia%2C%20the%20free%20encyclopedia,process%20g...

Allow Likert-type scale data to be used to automatically generate k*k pairwise comparisons, then populate a k x k square by summing the columns, to populate a k x k square matrix, and take the geometric mean of each row, then normalize the geometr...

In a linear hierarchy regression, it is important to know the change in R-squared to know if additional variables in a model increase the association with the predictor variables between the models (independent variables).

Would be nice to be able to integrate the area under the curve in linear and non-linear models.

I think will be very interesting if the NIPALS computation will be possible in all missing data selection

I think XLSTAT provides partial least squares models but not general least squares. This would be very practical for time series analysis, for instance.

In the procedure Similarity /Dissimilarity matrices but also in Cluster Analysis it is possible to use a variety of similarity and dissimilarity measures. Choosing the right one is most important. To understand all these measures it would be han...