Hello @Phoenix_LJ ,
I am assuming you are familiar with the backshift notation and polynomials in the backshift operator.
Here's the formulae of your ARIMA(1,0,1)(1,1,1)52 model :
- Z_t =
( 1 - B ) ( 1 - B**52 ) Y_t
- ( 1 - 0.90219B ) ( 1 + 0.05042B**52) Z_t = 0.071843 + (1 - 0.15713B ) ( 1 - 0.65111B**52 ) e_t
This is indeed a SARIMA model, i.e. Seasonal ARIMA (Auto-Regressive Integrated Moving Average) model with :
- seasonal differencing (once on 52 periods = simple seasonal differencing). The degree d of the seasonal differencing is 1 and s=52 is the length of the seasonal cycle.
- 1 is the order of the autoregressive part
- 1 is the order of the seasonal autoregressive part
- 1 is the order of the moving-average process
- 1 is the order of the seasonal moving-average process
- e_t is the independent disturbance, also called the random error
- you have no transfer functions as it is not SARIMAX (with some extra X-input time series)
Kind regards,
Koen