Does having a set of predictors which are not linearly separable slow down the model fit in STAN? If so, why?
I have tried to test this, and it appears to slow down the fit. I fit a model with 10,000 rows and 61 linearly separable columns except for the intercept, 100 iterations for two chains and it finished in 7 minutes.
I fit a model with 61 columns which had columns which were linear combinations and it has taken over 18 minutes to finish the first chain.