PyMC-DRAM

This package implements a Delayed Rejection Adaptive Metropolis sampler in PyMC 2.

Installing

• Install PyMC 2
• Clone this repository
• python setup.py install or python setup.py develop (you may need sudo too)

Use

import pymc as P
from pymc_dram import DRAM

NS = ...

# do initialization stuff
...

# construct model
def model_factory():
    ...
    return locals()

mvars = model_factory()
M = P.MCMC(mvars)

M.use_step_method(
    DRAM,
    [x for (_, x) in mvars.items()],
)

M.sample(NS, burn=NS / 2.)

# analyze chains
...

For a more complete example, see test_model.py. This recreates the results of Example 8.2 in Uncertainty Quantification: Theory, Implementation, and Applications by Ralph Smith.

To get a list of parameters you can pass to the sampler, see the docstring (help(DRAM) in the interpreter or browse the source). The default parameters should be fine for most users.

Notes

This only computes one delayed rejection step. It could be extended to add more but it seems most implementations don't bother and it adds significant complexity for marginal benefits.

License

This software shares the same license as PyMC, the Academic Free License 3.0, see LICENSE.

Credit

This code is adapted from an initial implementation by Kyle Huston (@khuston), see the credits file.