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Bayesian mixing models to analyze biotracer data (i.e. stable isotopes, fatty acids) Ref: https://github.com/brianstock/MixSIAR

I would like to examine the nodes and splitting rules for each of the trees generated for a random forest, along with the bootstrapped sample and features selected to train that tree. Can I get to those details?

Introduction of kernel functions in PLS can significantly improve the explanatory power of regression. Hope it comes true in future.

It would be helpful to analyze financial problems such as projecting dividend growth

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.

Are there any possibilities for stacking multiple plots, vertically with the same X axis but different Y axes using XLSTAT?

see above