Blurb::
Suppresses output of sensitivity indices with values lower than this tolerance
Description::
The ``drop_tolerance`` keyword allows the user to specify a value below
which sensitivity indices generated by ``variance_based_decomp`` are
not displayed.

*Default Behavior*

By default, all sensitivity indices generated by
``variance_based_decomp`` are displayed.

*Usage Tips*

For ``polynomial_chaos``, which outputs main, interaction, and total
effects by default, the ``univariate_effects`` may be a more
appropriate option.  It allows suppression of the interaction effects
since the output volume of these results can be prohibitive for high
dimensional problems. Similar to suppression of these interactions is
the covariance control, which can be selected to be
diagonal_covariance or full_covariance, with the former supporting
suppression of the off-diagonal covariance terms (to save compute and
memory resources and reduce output volume).
Topics::

Examples::

.. code-block::

    method,
      sampling
        sample_type lhs
        samples = 100
        variance_based_decomp
        drop_tolerance = 0.001


Theory::

Faq::

See_Also::
