Will Stan work well with 40×40 matrices?

Tomas Iesmantas writes:

I’m dealing with high dimensional (40-50 parameters) hierarchical bayesian model applied to nonlinear Poisson regression problem.

Now I’m using an adaptive version for the Metropolis adjusted Langevin algorithm with a truncated drift (Yves F. Atchade, 2003) to obtain samples from posterior.

But this algorithm is not very efficient in my case, it needs several millions iterations as burn-in period. And simulation takes quite a long time, since algorithm has to work with 40×40 matrices.

Maybe you know another MCMC algorithm which could take not so many burn-in samples and would be able to deal with nonlinear regression? In non-hierarchical nonlinear regression model adaptive metropolis algorithm is enough, but in hierarchical case I could use something more effective.

My reply:

Try fitting the model in Stan. If that doesn’t work, let me know.

8 thoughts on “Will Stan work well with 40×40 matrices?

  1. Stan is like the tooth fairy. The procedure is that you carefully write out your posterior on $50 bank notes and place it under your pillow. Post your home address and location of the bedroom here, and make sure you leave your door unlocked when you go to sleep.

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