Combining Evidence Across Filtrations
We address an intriguing challenge for sequential anytime-valid inference that arises when combining evidence processes constructed in different information sets. Accepted to JRSS-B.
Forecast Evaluation
Comparing Sequential Forecasters
We develop anytime-valid inference methods for estimating & testing the time-varying mean score difference between two sequential forecasters. Published in Operations Research.