Simulation-Based Prior Knowledge Elicitation for Parametric Bayesian Models

arXiv:2308.11672v2 Announce Type: replace-cross
Abstract: A central characteristic of Bayesian statistics is the ability to consistently incorporate prior knowledge into various modeling processes. In this paper, we focus on translating domain expert knowledge into corresponding prior distributions over model parameters, a process known as prior elicitation. Expert knowledge can manifest itself in diverse formats, including information about raw data, summary statistics, or model parameters. A major challenge for existing elicitation methods is how to effectively utilize all of these different …

abstract arxiv bayesian domain domain expert expert focus knowledge manifest modeling paper parameters parametric prior process processes simulation statistics stat.me stat.ml type