Randomized selective inference
Event details
Date | 28.06.2024 |
Hour | 15:15 › 16:15 |
Speaker | Daniel Garcia Rasines, Imperial College London |
Location | |
Category | Conferences - Seminars |
Event Language | English |
In contemporary statistical applications, selection of the formal inferential problem is typically done after some level of interaction with the data. Usually, an initial exploratory analysis is used to identify interesting aspects of the population under study, and then the same dataset is used to learn about them. Such “data snooping” invalidates classical inferential procedures. Many approaches have been proposed to ensure inferential validity in these settings.
In this talk, I will present an alternative to data splitting based on randomization which allows for higher selection and inferential power. I will describe the theoretical and empirical advantages of this method and discuss some related problems of current interest.
Practical information
- Informed public
- Free
Organizer
- Anthony Davison
Contact
- Maroussia Schaffner