It s great that you have the SVM included but in order to be actually useful for research these are the things that are needed for optimum model selection. Now the models are not optimized. 1. Cross-Validation: you need to add a k-fold cross-vali...

To predict the Overall Liking resulted from decreasing the percentages of Too Weak or Too Strong. This method would help clients in prioritizing sensory aspects to improve.

The Nash-Sutcliffe efficiency , Willmott's index and Model Performance Index (MPI) are suitable indices to add XLSTAT for assessing model performance.

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

In the {Significance by cell (Fisher's exact test)} table, we can only get < or >.It would be valuable to have the corresponding p-values per cell.

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

Spatial Autocorrelation Indices (e.g Moran's I) are mainstream of spatial statistics that are worth being implemented in XLSTAT software. They are useful for ecological studies.

important to know how many subjects are at risk at each major time interval. I have to look this up in the table and add it manually for each group being analyzed.

Allows running a multivariate ANOVA while controlling for covariates. Especially useful in consumer research to understand consumer behaviour when exposing subjects to more than one independent variable (combinations of two treatments) but simulta...

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 !