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...

I'm a very happy and satisfied customer using XLSTAT. I've recently upgraded to MS Office 365 and was hoping that you could guide me to an App, or the process by which I can continue to use my XLStat with the online of MS Excel.

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.

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.

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.

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.

Detrended Correspondence Analysis (DCA) is a popular multivariate analysis tool that is widely used to explore potentially sparse community data matrices in ecology. It is usually able to remove undesired arch effects.

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).