.. _method-bayes_calibration-queso-dram:

""""
dram
""""


Use the DRAM MCMC algorithm



**Topics**


bayesian_calibration


.. toctree::
   :hidden:
   :maxdepth: 1



**Specification**

- *Alias:* None

- *Arguments:* None

- *Default:* dram


**Description**


The type of Markov Chain Monte Carlo used.  This keyword specifies the
use of DRAM, (Delayed Rejection Adaptive Metropolis) :cite:p:`Haario`.

*Default Behavior*

Five MCMC algorithm variants are supported: ``dram``,
``delayed_rejection``, ``adaptive_metropolis``, ``metropolis_hastings``, and
``multilevel``.  The default is ``dram``.

*Usage Tips*

If the user knows very little about the proposal covariance, using
dram is a recommended strategy.  The proposal covariance is adaptively
updated, and the delayed rejection may help improve low acceptance
rates.



**Examples**



.. code-block::

    method,
            bayes_calibration queso
              dram
              samples = 10000 seed = 348




