Blurb::
Variance applied to simulation responses
Description::
The variance that is applied to simulations run by Dakota, i.e. using the
``analysis_drivers`` command. The user may supply a single variance
or a vector of variances of length equal to the number of responses. In both
cases, the values provided are treated as scalar variance types. If a single
variance is provided, it is applied to all responses produced by the
simulation code. If a vector is provided, each variance is applied to the
corresponding response output produced by the simulation code.

It is important to note that the the variance defined by this keyword differs
from that defined using ``experiment_variance_type``. These two commands apply
to user-provided calibration data, specified, for example, by
``calibration_data`` or ``calibration_data_file``. However, ``simulation_variance``
applies to those responses produced by simulation code that is run by Dakota,
as described above.

*Usage Tips*

Currently, this keyword is only in use as part of the algorithm implemented by
:dakkw:`method-bayes_calibration-experimental_design`. In this algorithm, two
models (usually, one high-fidelity and one low-fidelity) are provided to
Dakota, each with their own ``responses`` section of the input script, and each
of which is allowed its own ``simulation_variance``.
The variance specified in the ``responses``
block belonging to the high-fidelity model is applied to any <i> new </i>
high-fidelity data that is produced by Dakota running the high-fidelity model.
In the ``experimental_design`` algorithm,
low-fidelity model responses are used during the calibration of the model
parameters, the calculation of the mutual information, and the
calculation of any posterior statistics after the algorithm is complete. The
``simulation_variance`` is applied to the low-fidelity model responses that are
used in the calculation of the mutual information. See the User's and Theory
Manuals for more information.
Topics::

Examples::
The example below shows two ``responses`` blocks, one for the low-fidelity
model and one for the high-fidelity model. Both contain ``simulation_variance``
commands that will apply to the low- and high-fidelity model responses,
respectively.


.. code-block::

    responses,
      id_responses = 'low-fidelity'
     calibration_terms = 1
     simulation_variance = 0.5
    
    responses,
      id_responses = 'high-fidelity'
      calibration_terms = 1
     calibration_data_file = 'dakota_bayes_expdesign.dat'
       freeform
       num_config_variables = 1
       num_experiments = 1
       experiment_variance_type = 'none'
     simulation_variance = 1.2


Theory::

Faq::

See_Also::
