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Dakota Reference Manual
Version 6.15
Explore and Predict with Confidence
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The number of samples used in Monte Carlo approximation of the model evidence.
Alias: none
Argument(s): INTEGER
The 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 evidence_samples
keyword. Note that each sample specified by the 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.
Default Behavior
If evidence_samples
is not specified with mc_approx
, Dakota uses the number of chain samples from the MCMC (chain_samples
) as the number of samples to use for calculating the model evidence.
Expected Output Currently, the model evidence will be printed in the screen output with prefacing text indicating if it is calculated by Monte Carlo sampling.
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