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ARIMA(p, d, q) time-series model — estimation, forecasting, and prediction intervals.
Mirrors statsmodels.tsa.arima.model.ARIMA.
new ARIMAModel({ p, d, q }) constructs the model;
.fit(y) estimates the parameters using the Hannan-Rissanen
two-step method and returns coefficients, sigma², AIC, and BIC.
model.forecast(steps) returns point forecasts and 95 % prediction
intervals computed via ψ-weight recursion.
Combine AR and MA terms. ARMA(1,1): x_t = φ x_{t−1} + θ ε_{t−1} + ε_t.
Set d=1 for I(1) series (random walk, stock prices, etc.).
The model differences the series before fitting.
fitArima convenience function
fitArima(y, opts) is a one-liner shorthand for constructing
and fitting an ARIMA model.