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:
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.
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?
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.