Past event

JJ Valletta Memorial Lecture in Statistics and Data Science Emulation-driven inference for complex spatial meta-population model by Dr T J McKinley

This seminar is designed to be of wide interest to those curious about data science, statistics, and disease modelling. It will be given by Dr TJ McKinley of the University of Exeter. An abstract is given below. After the lecture, there will be an informal reception in the Mathematical Institute. All are welcome.

Abstract: Calibration of complex stochastic infectious disease models is challenging. These often have high-dimensional input spaces, with the models exhibiting complex, non-linear dynamics. Coupled with this is a paucity of necessary data, resulting in a large number of hidden states that must be handled by the inference routine.

Likelihood-based approaches to this missing data problem are very flexible, but challenging to scale due to having to monitor and update these hidden states. Methods based on simulating the hidden states directly from the model-of-interest have the advantage that they are often much more straightforward to code, and thus are easier to implement and adapt to changing model structures. However, they often require very large numbers of simulations in order to adequately explore the input space, which can render them infeasible for many large-scale problems.

This seminar will be given in the memory of our colleague JJ Valetta, who died suddenly while hillwalking on 25 October 2020.

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