Stats4Grads: Bayesian emulation and its application to analysing chemical interactions in biological plant models.
27 April 2016 13:00 in CM105
Many processes in our world are represented in the form of complex simulator models. These models frequently take large amounts of time to run. Emulators are statistical approximations of these simulators that make predictions, along with corresponding uncertainty estimates, of what the simulator would produce. The main advantage of these emulators is the speed at which they run, which, in general, is many orders of magnitude faster than the simulators which they aim to approximate. Emulation can be used in any area of science that represents real-world systems in the form of complex models.
I will provide an accessible introduction to the ideas of Bayesian emulation and history matching. I will then explain my application of Bayesian history matching by emulation in the context of biological plant models, and in particular a model of the chemical interaction network in the roots of the plant Arabidopsis. I will explain some of the practical difficulties of emulating such a complex biological model before showing some of the results I have thus far achieved. I will finally discuss briefly the idea of using these emulation techniques in the future design of actual biological experiments.
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See the Stats4Grads page for more details about this series.