For interpreting MDS solutions it is crucial to assess to what extent we are observing structure in the data instead of noise posing as structure. The use of Kruskal's "stress" has been criticized for this purpose, as this measure was conceived fo...

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.

Very useful when I need to understand relationships between 2 or 3 samples. And it would prevent me from spending hours on PowerPoint ! Thanks

k-fold cross validation and LOO are very efficient validation tools

More info regarding conditional probabilities

add some plot to show the panel's repeatability , consistency

it would be usefull

Upon performing AHC analysis, with your trail software , the groups resulted in the dendogram are colored , and it differs from those resulted in other statistical analysis, so we want to refer for that group with a certain color, how can we chang...