I am trying to use principal component analysis (PCA) to reduce dimensionality before applying linear regression. The problem is that my first 10 components are so weak (explaining only tiny variances - the 10th component's cumulative is 0.2577). What else could I try to apply the PCA?
Also I understand the whole process is referred to as principal component regression (PCR). Is there a tutorial or example I could learn in Stata/R?