What is SARIMA and how is it different from ARIMA?
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Answer ( 1 )
The ARIMA model is ARIMA(p,d,q)
where p = no of previous lags which are significant in determining present value.
d = The order of differencing you need to do to make the time series stationary.
q = The no of error terms in the previous lags which are significant in determining the present value.
SARIMA differs from ARIMA in seasonal component.
If your time series has a seasonal component then the values of p,d,q can be different
for the period of the seasonality.
ARIMA(p,d,q)*ARIMA(P,D,Q)S
where p = non-seasonal AR order, d = non-seasonal differencing, q = non-seasonal MA order,
P = seasonal AR order, D = seasonal differencing, Q = seasonal MA order,
and S = time span of repeating seasonal pattern.