Confidence ellipses in pca illustrate the dissociation of groups and aid in the recognition of trends.

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.

The Tanimoto coefficient is the most widely used similarity metric in cheminformatics.

It is useful in terms of crossvalidating the results and is implemented in other software

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...

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. ...

Data is becoming ever more both high dimensional and sparse. Kernel PCA can enable a reliable and relatively simple dimensionality reduction. Kernels have already been introduced in Xlstat via SVMs.

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...

Spatial data stats is perhaps the most important aspect in ecology but also for geochemistry, environmental research, conservation. At least some basic tests should be provided:Clark and Evans' R, Pielou's α, etc.