  A novel methodology to analyze non-Gaussian probability distribution
functions (PDFs) of intermittent turbulent transport in global full-f
gyrokinetic simulations is presented. In this work, the Auto-Regressive
Integrated Moving Average (ARIMA) model is applied to time series data of
intermittent turbulent heat transport to separate noise and oscillatory trends,
allowing for the extraction of non-Gaussian features of the PDFs. It was shown
that non-Gaussian tails of the PDFs from first principles based gyrokinetic
simulations agree with an analytical estimation based on a two fluid model.
