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...

Rolling multiple regression is extremely useful in that it enables you to see how stable the beta coefficients are over time. This is a very common issue that comes up regularly when you deal with financial time series.

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/

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.

Hello XLSTAT team. Any plans to add the eta squared and partial eta squared for ANOVA and regression ? These measures are commonly used to study the effect size. Plus, it is easy to implement and straightforward to interpret !

Dans un nuage de points, il peut être utile de visualiser par des lignes la moyenne, l'écart-type à 1 sigma et l'écart-type à 2 sigma pour chacune des variables.

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...

Very useful in geosciences.

affordable and simple option for making word clouds for instance...