masamichi

Dual Bayesian Regression Mutual cross-series interaction: Now you can simultaneously fit two time-series with full bidirectional (A↔B) Bayesian regression. Each series can be predicted while incorporating the influence of jumps in the other (via interaction terms). • Full model posterior (with HDI) for both A & B → Visualize effect sizes, uncertainties, and cross-causal coefficients. 🆕 Event...

Causality Probability (Positive Jump → Negative Jump): 0.40 Predicted Next Event: stable Time-Dependent Causality (lag steps → P): {1: 0.4, 2: 0.0, 3: 0.2, 4: 0.0, 5: 0.0, 6: 0.0, 7: 0.0, 8: 0.2, 9: 0.0, 10: 0.0} Hi Product Hunt! 👋 New Release！What’s New? 1. Causality Chain Detection Now automatically analyzes the causal probability that a positive jump (ΔΛC+) is followed by a negative jump...

Hi Product Hunt! 👋 I’m excited to share Lambda³, a history-aware Bayesian event detector for time series. Dual EYE Mode lets you see both global regime shifts and local anomalies—all fully explainable, not just “black-box” results. I built Lambda³ to make time series event detection transparent, collaborative, and easy to extend for any domain. If you have feedback, ideas, or want to contribute...