[RnD] Investigate Early Stopping in AA Tests

[tikhomirovd]

🚀 Feature Proposal

RnD: Investigate Early Stopping in AA Tests

Motivation

Currently, the AA test in HypEx does not include an early stopping mechanism. Introducing early stopping can help optimize experiment duration by identifying stable convergence points. However, it is essential to research when early stopping is valid, how to detect convergence effectively, and determine the best iteration for stopping without introducing bias.

Feature Description

• Conduct research on when early stopping can be applied in iterative AA tests.
• Analyze different stopping criteria (e.g., confidence interval stabilization, sequential testing methods, etc.).
• Determine the best iteration to stop the test based on statistical evidence.
• Document findings with recommendations for practical implementation.

Potential Impacts

• Reduced experiment runtime while maintaining statistical integrity.
• More efficient resource utilization for AA testing.
• Improved guidelines for early stopping in HypEx experiments.

Alternatives

• Continue running all iterations without early stopping (longer but stable testing).
• Use heuristics instead of rigorous statistical stopping criteria.

Additional Context

• Explore statistical techniques such as sequential analysis, Bayesian monitoring, and adaptive stopping.
• Compare results across different datasets to identify generalizable stopping conditions.
• Ensure findings align with best practices in experiment design.

Checklist

• Conduct research on early stopping criteria.
• Analyze when early stopping is statistically valid.
• Identify the optimal stopping iteration.
• Document findings and recommendations.
• Review and refine conclusions before implementation.