Hamiltonian MC with different variable dimensions

[junpenglao]

@N40

My intention is to use hmc as an alternative to Metropolis Hastings.

In that case, dynamic hmc like NUTS is your friend, just called pm.sample(1000, tune=1000) and let pymc3 try taking care of everything

@N40

Does that mean, that the mass matrix is adapted during the tuning session?

Yes

@N40

Do i need to run Hmc, NUTS or Metropolis in order to get an estimate for the mass matrix from the trace?

Well, you dont need to, as the mass matrix adaptation like pymc3 and Stan use a somewhat complex block sleep-wake update that is a pain to implement yourself (plus we already implemented and tested it)

@N40

If my covariance matrix (scaling matrix) is diagonal, does it simplyfy the problem?

Yes, in fact in pymc3 currently we are using diagonal mass matrix in the default

As for the arg to init the potential, i think this code snippet should clarify a bit:

pymc-devs/pymc/blob/4f67d639f984195f81b03cbfc19de64507f9f1f1/pymc3/sampling.py#L1542-L1547

But again, DO NOT use this option as it is suboptimal!