[Forum SIS] Seminar: "Bagging and blocking: Inference via particle filters for interacting dynamic systems", Edward Ionides, 23 November

[Umberto Picchini]

You are welcome to the next Statistics seminar at Dept of Mathematical 
Sciences at Chalmers and Göteborg University.

We are very glad to have, on Tuesday 23  November,​Edward Ionides(Uni. 
Michigan) who will talk of:

/"//Bagging and blocking: Inference via particle filters for interacting 
dynamic systems"/

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E. Ionides
*About the speaker*: Edward Ionides 
<http://dept.stat.lsa.umich.edu/~ionides/> is Professor of Statistics at 
the University of Michigan (U.S.). His main research interests are in 
time series analysis with applications including ecology, epidemiology 
and health economics. Methodological work on inference for partially 
observed stochastic dynamic systems.
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*Abstract: *Infectious disease transmission is a nonlinear partially 
observed stochastic dynamic system with topical interest. For 
low-dimensional systems, models can be fitted to time series data using 
Monte Carlo particle filter methods. As dimension increases, for example 
when analyzing epidemics among multiple spatially coupled populations, 
basic particle filter methods rapidly degenerate. A collection of 
independent Monte Carlo calculations can be combined to give a global 
filtering solution with favorable theoretical scaling properties. The 
independent Monte Carlo calculations are called bootstrap replicates, 
and their aggregation is called a bagged filter. Bagged filtering is 
effective at likelihood evaluation for a model of measles transmission 
within and between cities. A blocked particle filter also works well at 
this task. Bagged and blocked particle filters can both be coerced into 
carrying out likelihood maximization by iterative application to an 
extension of the model that has stochastically perturbed parameters. 
Numerical results are carried out using the R package spatPomp.
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*Feel free to spread this announcement in your network.*
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*Where*: https://chalmers.zoom.us/j/61599474564
Password: 939924
(locals are welcome in person in room MVL15)
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*When*: Tuesday 23 November at 14.15-15.15 (Swedish time).
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-- 
_________________________________________________________
Umberto Picchini, Associate Professor, PhD, Docent
https://umbertopicchini.github.io/  , twitter: @uPicchini
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