  The analysis of computer models can be aided by the construction of surrogate
models, or emulators, that statistically model the numerical computer model.
Increasingly, computer models are becoming stochastic, yielding different
outputs each time they are run, even if the same input values are used.
Stochastic computer models are more difficult to analyse and more difficult to
emulate - often requiring substantially more computer model runs to fit. We
present a method of using deterministic approximations of the computer model to
better construct an emulator. The method is applied to numerous toy examples,
as well as an idealistic epidemiology model, and a model from the building
performance field.
