Blurb::
Computes probabilities associated with response levels

Description::
The \c probabilities keyword directs Dakota to compute the probability that the model response will be below (cumulative) or above (complementary cumulative) a specified response value.  This is done for every response level designated for each response.

<b> Default Behavior </b>

If \c response_levels is specified, the probabilities are computed by default.  To explicitly specify it in the Dakota input file, though, the \c probabilities keyword should be specified in conjunction with the \c compute keyword.

<b> Expected Outputs </b>

The Dakota output is a set of response level-probability pairs that give the probability that the model response will be below or above the corresponding response level, depending on the distribution defined.

Topics::	
Examples::
\verbatim
method
  sampling
    sample_type random
    samples = 100 seed = 1
    complementary distribution
    response_levels = 3.6e+11 4.0e+11 4.4e+11
                      6.0e+04 6.5e+04 7.0e+04
                      3.5e+05 4.0e+05 4.5e+05
    compute probabilities
\endverbatim
Theory::
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