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

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

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 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).

Hello XLSTAT team. Any plans to add the eta squared and partial eta squared for ANOVA and regression ? These measures are commonly used to study the effect size. Plus, it is easy to implement and straightforward to interpret !

Robust PCA is as the name implies a more robust version of PCA. Extremely useful for large but sparse datasets (many biological areas e.g. ecology, metabolomics, transcriptomics; and computer science e.g. visual recognition).Provides a PCA which i...

It would be useful to have a function that is able to do logratio transformations (additive logratio (alr), centered logration (clr) and Isometric logratio (ilr) transformations). It is an important step in order to open up closed data (e.g. compo...

Here is a series of references for checking for groups of outliers in the data: https://lemakistatheux.wordpress.com/category/tests-statistique-indices-de-liaison-et-coefficients-de-correlation/les-tests-pour-la-detection-doutliers/

Upon performing AHC analysis, with your trail software , the groups resulted in the dendogram are colored , and it differs from those resulted in other statistical analysis, so we want to refer for that group with a certain color, how can we chang...

Adaptive Boosting (AdaBoost) could be very useful when synthesizing the info provided by several supvervised Machine Learning algorithms.