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

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

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...

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 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...

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

While automatically transferring the result sheet to a Word document, if the title in the transferred Word page uses sheet name it would be magnificent. Then user all has to do is to save the Word document with the sheet name. While writing the ar...

When performing the Kruskal-Wallis analysis of variance on k samples, up until now, you can choose between Dunn, Conover-Iman and Steel-Dwass-Critchlow-Fligner with the addition of Bonferroni correction (for the first two mentioned, respectively) ...