Blurb::
Perform Bayesian inference in standardized probability space
Description::
This option transforms the inference process (MCMC sampling
and any emulator model management) into a standardized probability space.

The variable transformations performed are as described in
:dakkw:`method-polynomial_chaos-askey`.

*Default Behavior*

The default for the Gaussian process and no emulator options is to
perform inference in the original probability space (no
transformation).  Polynomial chaos and stochastic collocation
emulators, on the other hand, are always formed in standardized
probability space, such that the inference process is also performed
in this standardized space.

*Expected Output*

The user will see the truth model evaluations performed in the
original space, whereas any method diagnostics relating to the MCMC
samples (e.g., QUESO data in the outputData directory) will report
points and response data (response gradients and Hessians, if present,
will differ but response values will not) that correspond to the
transformed space.

*Usage Tips*

Selecting standardized_space generally has the effect of scaling the
random variables to be of comparable magnitude, which can improve the
efficiency of the Bayesian inference process.
Topics::

Examples::

.. code-block::

    method,
            bayes_calibration queso
              samples = 2000 seed = 348
              dram
              standardized_space


Theory::

Faq::

See_Also::
