Blurb::
The number of samples used in Monte Carlo approximation of the model evidence. 

Description::
The \c mc_approx keyword for model evidence indicates that 
sample values will be generated from the prior distribution,
and then the simulation model will be evaluated at these 
sample values to obtain corresponding likelihood values. 
The average of the likelihood weighted by the prior is the 
model evidence. The accuracy of this approximation depends on the 
number of samples taken, which is specified by 
the \c evidence_samples keyword. 
Note that each sample specified by the \c evidence_samples keyword 
will require an evaluation of the simulation model to compute the 
corresponding likelihood. So, this may become costly for expensive 
simulations.  Additionally, many prior samples will have very low 
(near zero) likelihood, so millions of samples may be required for 
accurate computation of the integral which defines model evidence. 

<b> Default Behavior </b>

If \c evidence_samples is not specified with \c mc_approx, Dakota 
uses the number of chain samples from the MCMC (\c chain_samples) 
as the number of samples to use for calculating the model evidence. 

<b> Expected Output </b>
Currently, the model evidence will be printed in the screen output 
with prefacing text indicating if it is calculated by 
Monte Carlo sampling.

<b> Usage Tips </b>


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