Abstract: Many computer models, including climate prediction models such as C-goldstein and economic models such as E3MG, take many hours, or even weeks, to execute. This type of model can have tens to hundreds of free (adjustable) parameters, each of which is only approximately known. Under the Bayesian view, the true value of the code output is a random variable, drawn from a distribution that is conditioned by our prior knowledge, and in this case by the previous code runs; the computer code is thus viewed as a random function.

In this informal talk, I introduce the BACCO suite of software and show how it can be used to generate statistical inferences about such random functions. The software may be used to furnish computationally cheap