Academy of Finland  
Funding decision
Organisation Aalto University
Project title Safe iterative Bayesian model building
Applicant / Contact person Vehtari, Aki
Decision No. 340721
Decision date 03.06.2021
Funding period 01.09.2021 - 31.08.2025
Funding 531 066
Project description
Statistical analysis is critical when it comes to obtaining insights from data. Despite the practical success of iterative Bayesian statistical model building, it has been criticized to violate pure Bayesian theory and that we may end up with a different model had the data come out differently. In this project, we formalize and develop theory and diagnostics for safe iterative Bayesian model building. We show that when the iterative model building is done carefully, the difference to the theoretically optimal result is negligible. The practical diagnostics guide the modeller through the appropriate steps to ensure safe iterative model building, or indicate when the modeller is likely to be in the danger zone. By making applied scientific research and data analysis in private and public sectors more reliable and reproducible, our understanding of the world and decision-making will be improved. Thus, the project will have a long lasting positive impact on society.