Skip to content

Instantly share code, notes, and snippets.

View alfred-landrum's full-sized avatar

Alfred Landrum alfred-landrum

  • San Francisco, CA
View GitHub Profile
@alfred-landrum
alfred-landrum / README.md
Last active August 29, 2015 14:14 — forked from welch/README.md

Smooth

Exponential smoother/forecaster with de-seasonalization

Smooth models an unobserved level and trend component in a noisy signal, along with optional "seasonal" effects at the level of day-over-day variation. The result is a smoothed version of the signal which may be used to forecast future values or detect unexpected variation.

In this example, we apply our smoother to a sample 10-day timeseries published in Twitter's AnomalyDetection package. The series is 10 days of counts, with a regular daily pattern and occasional surprises (spikes and dips). The Juttle output focuses on the three days around Oct 1.