Among the sessions I attended yesterday, I really liked the one on robustness and model mispecification. Especially the talk by Steve McEachern on Bayesian inference based on insufficient statistics, with a striking graph of the degradation of the Bayes factor as the prior variance increases. I sadly had no time to grab a picture of the graph, which compared this poor performance against a stable rendering when using a proper summary statistic. It clearly relates to our work on ABC model choice, as well as to my worries about the Bayes factor, so this explains why I am quite excited about this notion of restricted inference. In this session, Chris Holmes also summarised his two recent papers on loss-based inference, which I discussed here in a few posts, including the Statistical Science discussion Judith and I wrote recently. I also went to the j-ISBA [section] session which was sadly under-attended, maybe due to too many parallel sessions, maybe due to the lack of unifying statistical theme.
This entry was posted on June 16, 2016 at 12:16 am and is filed under pictures, Running, Statistics, Travel, University life, Wines with tags ABC, approximate likelihood, Calasetta, ISBA 2016, j-ISBA, loss function, restricted inference, San' Antioco, Sardinia, Statistical Science, summary statistics. You can follow any responses to this entry through the RSS 2.0 feed.
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Steve’s talk is my favourite so far. Loved the content. Loved the delivery!
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