Blurb::
Utilize the logit transformation to reduce sample rejection for bounded domains
Description::
The logit transformation performs an internal variable transformation from bounded domains to unbounded domains in order to reduce sample rejection due to an out-of-bounds condition.

*Default Behavior*

This option is experimental at present, and is therefore defaulted off.

*Usage Tips*

This option can be helpful when regions of high posterior density exist
in the corners of a multi-dimensional bounded domain.  In these cases,
it may be difficult to generate feasible samples from the proposal density,
such that transformation to unbounded domains may greatly reduce sample
rejection rates.
Topics::

Examples::

.. code-block::

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


Theory::

Faq::

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