Examines the model's parameters for stability constraints (e.g. stationary, invertibility, causality, etc.).
mean is the model mean (i.e. mu).
sigma is the standard deviation of the model's residuals/innovations.
s is the length of seasonality (expressed in terms of lags, where s > 1).
theta is the coefficient of first-lagged innovation (see model description).
theta2 is the coefficient of s-lagged innovation (see model description).
- The underlying model is described here.
- The standard deviation (i.e. $\sigma$) of the ARMA model's residuals should be greater than zero.
- The Airline model is a special case of multiplicative seasonal ARIMA model. The model assumes independent and normally distributed residuals with constant variance.
- The AIRLINE_CHECK examines the MA coefficients: $\theta, \Theta, \theta\times\Theta$ for process stability.
|=AIRLINE_AIC(Sheet1!$B$2:$B$15,1,$D$3,$D$6,$D$7,$D$4,$D$5)||65.6||Akaike's information criterion (AIC)|
|=AIRLINE_CHECK($D$3,$D$6,$D$7,$D$4,$D$5)||1||Is the AIRLINE model stable?|