GARTFIMA models combine observation-driven generalized linear models with tempered fractional differencing to capture semi-long memory in non-Gaussian time series.
Forecasting the proportion of stored energy using the unit Burr XII quantile autoregressive moving average model
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GARTFIMA Models: A Class of Observation-Driven Models with Tempered Fractional Dynamics
GARTFIMA models combine observation-driven generalized linear models with tempered fractional differencing to capture semi-long memory in non-Gaussian time series.