Here's the situation: I am trying to build a model to express a particular Y using 25 parameters in X. All the data from my parameters X is given by the same single technology, which is analyzing 1 sample using 25 frequencies (my X), as a frequency scanning to gain maximum information. In other word, for each single Y data, I will have 25 X.
But the issue is that when I build models, I obtain huge VIFs because my parameters X are inherently collinear as they are just frequencies of the same technology so they evolve the same way ...
And if I do as I learned, meaning removing each parameters one by one based on the highest VIF I end up with one single frequency left, which removes all the interest of the scanning technology.
In that particular case, is the model really biaised by these colinearities or can we trust it?
@alexbeck maybe?
