Find the best combination of AR(k) estimation method and scoring function

[takuti]

ref #11

• AR(k) estimation method
  • Burg's method
  • Yule-Walker
• Scoring function
  • Logloss
  • Hellinger distance

Which combination is the best on the real-world DD metrics and use-cases?

• [x] Both of them should be configurable
• [x] Test all possible cases on the synthetic and twitter data
• [ ] Upload a notebook for further comparison
• [x] Test on the aggregated real DD data points
• [ ] Deploy and monitor whether the combination works as expected
  • If not, why? How can we solve the problem?

[takuti]

Synthetic

r=0.02, k=6, T1=10, T2=5

Twitter

r=0.03, k=6, T1=10, T2=5

[takuti]

Datadog aggregated data points of a sample metric

• r=0.03, k=6, T1=10, T2=5 for LogLoss
• r=0.09 for Hellinger