I have time series with frequency=7.
ndiffsfunction (https://www.rdocumentation.org/packages/forecast/versions/8.10/topics/ndiffs) suggests first order difference .
kpss.test from tseries package (https://www.rdocumentation.org/packages/tseries/versions/0.10-47/topics/kpss.test) suggests first order difference as well for (null="Trend"), while
nsdiffs function tells that seasonal difference is not required. (https://www.rdocumentation.org/packages/forecast/versions/8.10/topics/nsdiffs).
ACF GRAPH of the series.
After the first order difference the following ACF and PACF graphs are constructed:
It looks stationary and passes previously mentioned unit root tests, but ACF and PACF graphs made me thinking.
Seasonality doesn't appear to die out in ACF graph. My question is: what should I do with it ? Is seasonal difference required or should I just model it with ARIMA(p,1,q)(P,0,0)7 model, where p,q and P parameters are modeled to minimize AIC?