.. _method-bayes_calibration-muq-dram:

""""
dram
""""


Use the DRAM MCMC algorithm



**Topics**


bayesian_calibration


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

   method-bayes_calibration-muq-dram-num_stages
   method-bayes_calibration-muq-dram-scale_type
   method-bayes_calibration-muq-dram-delay_scale
   method-bayes_calibration-muq-dram-period_num_steps
   method-bayes_calibration-muq-dram-starting_step
   method-bayes_calibration-muq-dram-adapt_scale


**Specification**

- *Alias:* None

- *Arguments:* None

- *Default:* dram


**Child Keywords:**

+-------------------------+--------------------+----------------------+-----------------------------------------------+
| Required/Optional       | Description of     | Dakota Keyword       | Dakota Keyword Description                    |
|                         | Group              |                      |                                               |
+=========================+====================+======================+===============================================+
| Optional                                     | `num_stages`__       | Number of stages                              |
+----------------------------------------------+----------------------+-----------------------------------------------+
| Optional                                     | `scale_type`__       | Type of scaling to use                        |
+----------------------------------------------+----------------------+-----------------------------------------------+
| Optional                                     | `delay_scale`__      | Scaling parameter                             |
+----------------------------------------------+----------------------+-----------------------------------------------+
| Optional                                     | `period_num_steps`__ | Number of steps between updates of the        |
|                                              |                      | proposal covariance                           |
+----------------------------------------------+----------------------+-----------------------------------------------+
| Optional                                     | `starting_step`__    | Number of steps prior to start of proposal    |
|                                              |                      | covariance adaptation                         |
+----------------------------------------------+----------------------+-----------------------------------------------+
| Optional                                     | `adapt_scale`__      | Sample covariance scaling used to define      |
|                                              |                      | proposal covariance                           |
+----------------------------------------------+----------------------+-----------------------------------------------+

.. __: method-bayes_calibration-muq-dram-num_stages.html
__ method-bayes_calibration-muq-dram-scale_type.html
__ method-bayes_calibration-muq-dram-delay_scale.html
__ method-bayes_calibration-muq-dram-period_num_steps.html
__ method-bayes_calibration-muq-dram-starting_step.html
__ method-bayes_calibration-muq-dram-adapt_scale.html



**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