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Thread: Understanding ARIMA

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    Question Understanding ARIMA

    I am trying to decompose time series contains approx. 120 observations.
    Using ARIMA(p,d,q) model I need to find three parameters:
    d - this one I found, by differencing once the observations (hence the mean and variance have turned pretty constant over time).
    As to the other two: p, q - I have been using R's functions ACF and PACF in order to examine autocorrelation and partial autocorrelation, respectively.
    In the attach files you can see the both plots - where the x axis represents number of lags (I chose 10 lags).
    Could anyone help with identifying what should I use for p and q?
    Hope my question is clear,
    Attached Thumbnails Attached Thumbnails Click image for larger version

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