Here are the slides of my talk yesterday at the Computational Methods in Applied Sciences workshop in Columbia:
The last section of the talk covers our new results with Jean-Michel Marin, Natesh Pillai and Judith Rousseau on the necessary and sufficient conditions for a summary statistic to be used in ABC model choice. (The paper is about to be completed.) This obviously comes as the continuation of our reflexions on ABC model choice started last January. The major message of the paper is that the statistics used for running model choice cannot have a mean value common to both models, which strongly implies using ancillary statistics with different means under each model. (I am afraid that, thanks to the mixture of no-jetlag fatigue and of slide inflation [95 vs. 40mn] and of asymptotics technicalities in the last part, the talk was far from comprehensible. I started on the wrong foot with not getting an XL [Xiao-Li’s] comment on the measure-theory problem with the limit in ε going to zero. A peak given that great debate we had in Banff with Jean-Michel, David Balding, and Mark Beaumont, years ago. And our more recent paper about the arbitrariness of the density value in the Savage-Dickey paradox. I then compounded the confusion by stating the empirical mean was sufficient in the Laplace case…which is not even an exponential family. I hope I will be more articulate next week in Zürich where at least I will not speak past my bedtime!)
