Xi'an's Og

For the final talk of this Spring season of the One World ABC webinar, we are very glad to welcome Marc Beaumont, a central figure in the development of ABC methods and inference! (And a coauthor of our ABC-PMC paper.)

Model misspecification in population genomic
Mark Beaumont
University of Bristol
30th May 2024, 9.00am UK time

Abstract
In likelihood-free settings, problematic effects of model misspecification can manifest themselves during computation, leading to nonsensical answers, particularly causing convergence problems in sequential algorithms. This issue has been well studied in the last 10 years, leading to a number of methods for robust inference. In practical applications, likelihood-free methods tend to be applied to the output of complex simulations where there is a choice of summary statistics that can be computed. One approach to handling misspecification is to simply not use summary statistics computed from simulations of the model under the prior that cannot be with those observed in the data. This presentation gives a brief review of methods for observing and handling misspecification in ABC and SBI, and then discusses approaches that we have explored in a population genomic modelling framework.

This entry was posted on May 17, 2024 at 12:24 am and is filed under Books, pictures, Statistics, Travel, University life with tags ABC, ABC consistency, ABC-PMC, computational statistics, likelihood-free methods, Mark Beaumont, misspecification, One World ABC Seminar, population genomics, population Monte Carlo, simulation, summary statistics. You can follow any responses to this entry through the RSS 2.0 feed. You can leave a response, or trackback from your own site.