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...

Could you please add XGboost as a new Machine Learning available algorithm?

In time series analysis, dynamic time warping (DTW) is one of the algorithms for measuring similarity between two temporal sequences, which may vary in speed. The ability to analyze and then cluster times series based on dynamic time warping wou...

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

Estimating lagged prediction models from autocorrelated historical data is a common challenge in business and economics. The resulting multicollinearity causes the models to perform poorly. The Almon lag method is a clever way to deal with the mul...

Hi, I am interested to explore regression tools in conjunction with Machine learning. Currently XLSTAT is not offering any regression solutions within Machine Learning. One of the areas to look into is SVM, where regression solutions are offered. ...

Given the cost of the software, it is dissapointing to see the XLSTAT-Forecast module does not include BASIC forecast evaluation statistics such as Diebold Mariano, Peseran-Timmerman, Correct Sign, RMSE, MSE, ME, MAE, MAPE etc - the first three st...

ARIMA model with possibility of adding external variables, this is a great forecast method. Can you add this model=

More info regarding conditional probabilities

It would be great to have the Savitzky-Golay derivative smoothing among the XLSTAT smoothing methods