Bayesian Methods for the Social Sciences

›9:00 (30min)

James Berger
The Empirical Error of P-values, E-values and Objective posterior probabilities

›9:30 (30min)

Eric-Jan Wagenmakers
Approximate objective Bayes factors from p-Values and sample size: The 3p \sqrt{n} rule

›10:00 (30min)

Zoltan Dienes
Using Bayes to severely test theories

›11:00 (30min)

Pierre Latouche
Bayesian Statistics, AI, and networks for the analysis of the last French presidential election

›11:30 (30min)

Nial Friel
Bayesian approaches for zero-inflated weighted networks

›12:00 (30min)

Sophie Donnet
Bayesian inference for a Poisson Stochastic Blockmodel for weighted social networks

›14:00 (30min)

Robin Ryder
Bayesian methods for Historical Linguistics

›14:30 (30min)

Zita Oravecz
Bayesian inference for dynamical models of emotion

›15:00 (30min)

Maarten Marsman
Structure learning of psychometric networks

›16:00 (2h)

Poster session