I'd like to apply SARIMA model to my time series. I'd like to know how I could determine/guess the parameters by using ACF and PACF graphs. The time series data range from years 1995 - 2020. The data is further divided into quarters of the year. The time series look like this:

enter image description here

It can be seen that there is an upward trend as well as seasonal one. The period for the seasonal trend seems to be 2 quarters or 8 months. Should q then be 2? And how do I know the Q? I am not sure about the p and P too.

The ACF and PACF graphs are confusing as well.

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The lags is measured as quarters of the year. So, every data point depends on 15 data points before it. Then that would make q = 15? and Q = 5?

Here is the PACF graph: enter image description here

I don't know how to interpret this one. The pacf shows which particular prior value contributes to the value at hand, graph seems to indicate that the value is 5, but that's 1 year and 8 months, from initial time series graph the period of the seasonal trend seem to be equal to two quarters.


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