So that people won't need another software

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...

Besides the mean comparisons between products or time-points, in consumer studies for example, usually Tops (1, 2, 3..) and Bottoms proportions/percentages are also required. As the number of questions is usually large, the inclusion of the result...

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...

Here is a series of references for checking for groups of outliers in the data: https://lemakistatheux.wordpress.com/category/tests-statistique-indices-de-liaison-et-coefficients-de-correlation/les-tests-pour-la-detection-doutliers/

The scatterplot matrix is a great way to quickly visualize correlations among multivariate data. It is especially helpful if confidence ellipses can be added and if the axes can be easily edited.

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.

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...

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. ...