1Blurb:: 2Calculate model evidence using a Monte Carlo sampling approach 3 4Description:: 5The \c mc_approx keyword for model evidence indicates that 6sample values will be generated from the prior distribution, 7and then the simulation model will be evaluated at these 8sample values to obtain corresponding likelihood values. 9The average of the likelihood weighted by the prior is the 10model evidence. The accuracy of this approximation depends 11on the number of samples taken, which is specified by 12the \c evidence_samples keyword. 13 14<b> Default Behavior </b> 15 16If \c evidence_samples is not specified with \c mc_approx, Dakota 17uses the number of chain samples from the MCMC (\c chain_samples) 18as the number of samples to use for calculating the model evidence. 19 20<b> Expected Output </b> 21Currently, the model evidence will be printed in the screen output 22with prefacing text indicating if it is calculated by 23Monte Carlo sampling. 24 25<b> Usage Tips </b> 26 27 28Topics:: 29 30Examples:: 31 32Theory:: 33Faq:: 34See_Also:: 35