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sequential-testing

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Runs ~20 options strategies against live market data in shadow mode, records every hypothetical fill under worst/base/optimistic assumptions, and grades each with anytime-valid e-processes. Places no orders.

  • Updated Jul 22, 2026
  • Python
bayesdecide

Bayesian multi-armed bandits for continuous prompt experimentation: Thompson sampling routes traffic to the best prompt variant and a stopping rule promotes a winner without a fixed-N A/B test. Zero dependencies, TypeScript-first.

  • Updated Jun 22, 2026
  • TypeScript

Anytime-valid A/B test analyzer that holds the false-positive rate under 1.5% while you peek at the dashboard continuously, where naive fixed-horizon testing leaks to 23% at 15 looks. mSPRT with confidence sequences, CUPED variance reduction (50% on the demo, SE 0.223 to 0.135), a peeking guard, and a reproducible A/A simulation.

  • Updated Jul 27, 2026
  • Python

Always-valid sequential A/B testing engine: mSPRT confidence sequences make peeking safe by construction, CUPED cuts variance up to 49%, SRM gates bad data. Built-in adversarial peeking harness proves the claim: naive daily peeking hit 27.5% false positives in 2,000 simulations; this engine held 1.7%. All numbers reproducible from committed seeds.

  • Updated Aug 4, 2026
  • Python

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