Blurb::
Fit MLMC sample allocation to a mixture of terms of means and standard deviations.
Description::
Fit MLMC sample allocation to control the variance of the estimator for a mixture of terms of means and standard deviations. The exact scalarized formulation is given by the keyword ``scalarization_response_mapping``.
Topics::

Examples::
The following method block

.. code-block::

    method,
     model_pointer = 'HIERARCH'
            multilevel_sampling
       pilot_samples = 20 seed = 1237
       convergence_tolerance = .01
       allocation_target = scalarization
        scalarization_response_mapping = 1 0 0 0
                                                     0 0 1 3


uses the standard_deviation as sample allocation target by computing its variance. In this example, we assume a problem with two responses where the first line in scalarization_response_mapping refers to the first response, the second line to the second response. In the first line we only use 1 times the mean as quantity of interest. For the second response, we use 1 time the mean plus 3 times the standard devitation of the second quantity of interested. This behavior mimics the keywords :dakkw:`model-nested-sub_method_pointer-primary_response_mapping` and :dakkw:`model-nested-sub_method_pointer-secondary_response_mapping`.
Theory::

Faq::

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