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The first step in producing an accurate smoothing by the ARMA model is to find the best orders of the model for the pressure data.
The orders of the model were identified initially by the cut-off figure of the autocorrelation function (ACF) and the decay figure of the partial ACF PACFF).
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Therefore, the order of the model is greatly reduced.
The model coefficients are all real. is a positive integer defining the order of the model.
At the removal of a transmission line, the order of the model is reduced to 17.
To determine the order of the model, this paper uses AIC rules (Akaike 1969).
where, ‖x‖2 = x T x, and p is the order of the model (12).
Correlogram is a useful tool to provide optimum order of the model.
Next, we present a fast frequency-domain cross validation method for selecting the order of the model.
Component Mode Synthesis (CMS) methods allow one to reduce the order of the model at the subcomponent level.
In general, the order of the model depends on the measured site; however, the fifth-order process has been used as an upper bound [10].
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Justyna Jupowicz-Kozak
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