Examines the model's parameters for stability constraints (e.g., stationary, invertibility, causality, etc.).

## Syntax

**AIRLINE_CHECK** (µ, **σ**, **s**, θ, θ_{s})

**µ**- Optional. Is the model mean (i.e., mu) or the long-run mean of the differenced time series.
**σ**- Required. Is the standard deviation of the model's residuals/innovations.
**S**- Required. Is the length of seasonality (expressed in terms of lags, where s > 1).
**θ**- Optional. Is the coefficient of the non-seasonal MA component (see model description).
**θ**_{s}- Optional. Is the coefficient of the seasonal MA component (see model description).

## Remarks

- 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 a multiplicative seasonal ARIMA model. The model assumes independent and normally distributed residuals with constant variance.
- The AIRLINE_CHECK() function examines the MA coefficients: $\theta ,{\theta _s},\theta \times {\theta _s}$ for process stability.

## Files Examples

## Related Links

## References

- James Douglas Hamilton; Time Series Analysis, Princeton University Press; 1st edition(Jan 11, 1994), ISBN: 691042896.
- Tsay, Ruey S.; Analysis of Financial Time Series, John Wiley & SONS; 2nd edition(Aug 30, 2005), ISBN: 0-471-690740.

## Comments

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