I am trying to make time series analysis with SARIMA and I have a question. My dataset is a seasonal dataset. I validated that I have stationary series by KPSS test.
I also found the following results:
ndiffs(ts) #number of regular difference  0
nsdiffs(ts) #number of seasonal difference  1
According to the results, I took the seasonal difference of the dataset, then I drew ACF and PACF of differenced time series:
I think I couldn't make suitable model identification. I thought that following three model could fit the dataset.
SARIMA(1,0,1)(1,1,1) SARIMA(1,0,2)(1,1,1) SARIMA(1,0,3)(1,1,1)
However, when I summary of the three model I got the following results:
Also, I used
auto.arima but I found that model is insignificant as well.
I think I am missing something because I am very new to this field. Can somebody have an idea?
I also used seasonal dummy variables thanks to the advices of @richard As a result of regression, all seasonal dummies are significant and model has 95% R^2 value. When I draw the ACF and PACF functions of residuals of the regression model, I got the following plot: