Calculates the estimated error/standard deviation of the conditional mean forecast.
X is the univariate time series data (one dimensional array of cells (e.g. rows or columns)).
Order is the time order in the data series (i.e. the first data point's corresponding date (earliest date=1 (default), latest date=0)).
|1||ascending (the first data point corresponds to the earliest date) (default)|
|0||descending (the first data point corresponds to the latest date)|
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).
T is the forecast time/horizon (expressed in terms of steps beyond end of the time series).
- The underlying model is described here.
- Warning: AIRLINE_FORESD() function is deprecated as of version 1.63: use AIRLINE_FORE function instead.
- The time series is homogeneous or equally spaced.
- The time series may include missing values (e.g. #N/A) at either end.
|=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?|