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...

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).

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.

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.

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

So that people won't need another software

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

When performing the Kruskal-Wallis analysis of variance on k samples, up until now, you can choose between Dunn, Conover-Iman and Steel-Dwass-Critchlow-Fligner with the addition of Bonferroni correction (for the first two mentioned, respectively) ...

These are very important analysis in microbial ecology. Both analyses are critical to understanding the behaviour and relationship between microbial community; their population shift in response to treatment/environmental changes. The ability to...

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