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. ...

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

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

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...

More info regarding conditional probabilities

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

When selecting several time series for prediction in smoothing and ARIMA, XLSTAT generates one report per time series. It would be nice to have one summary table for all series at the bottom of the report (prediction & validation).