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Empirically, it was also shown that other variables in second stage V-IGARCH 1,1) V-IGARCH 1,1stationary.
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The unit root test results indicate that nearly all the variables in the acreage response models are stationary after first differencing at the 10%% level or less (Table 2).
Both variables in this two-stage V-IGARCH (1, 1) model were stationary in nature.
Compared to tree structured models, the (spatial) random process on the base level of the model is stationary which avoids known drawbacks, namely visual artifacts in the segmented image.
Both sinusoidal modeling and noise modeling assume that the signal segment being modeled is stationary.
According to [11], the optimal policy for an infinite discount Markov decision model is stationary.
If there is no advection, i.e., w t =0 and D=I, the model is stationary and isotropic.
The augmented Dickey-Fuller unit root test confirmed that the variables used in the model are stationary.
When one works with a single sequence, it is common to assume that the underlying model is stationary.
The results show that variables in the models were non-stationary and cointegrated (Table 2).
In addition, no-slip boundary condition was applied at the wall, as all these LAD models were assumed to be stationary and rigid.
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