Classical✓ Mathematical
◆ The PatternARIMA with seasonal intelligence
SARIMA(p,d,q)(P,D,Q)m adds seasonal AR, differencing, and MA terms at seasonal lag m. This captures repeating patterns at fixed intervals — weekly (m=7), monthly (m=12), quarterly (m=4).
SARIMA(p,d,q)(P,D,Q)m
Lowercase = non-seasonal orders. Uppercase = seasonal orders at lag m. The model simultaneously captures short-term dynamics and periodic patterns.
// Interactive — seasonal pattern visualization
Season (m)12
Seasonal Strength60
# Python — SARIMA from statsmodels.tsa.statespace.sarimax import SARIMAX model = SARIMAX(series, order=(1, 1, 1), seasonal_order=(1, 1, 1, 12)).fit() forecast = model.get_forecast(steps=24) ci = forecast.conf_int(alpha=0.05)
Pattern bridge: Seasonal patterns in time series are the same calendar seasonality that drives market cycles. The Fourier terms in SARIMA connect to Fourier analysis in ML Math.