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Fitting time dependent marginal distributions and time dependent copulas to the data sets, and comparing the results with the stationary approach, shows the influence of the non-stationary behavior of the variables.
The complex and coupled behavior of the variables that affect the currently developing generation IV reactors and the increase of interest in Small Modular Reactors are major incentives to seek efficient design methods.
The stochastic common trends represent the long-run behavior of the variables.
The behavior of the variables included in the VAR model is shown in Fig. 1.
The behavior of the variables analyzed is similar in both study groups.
It is seen that the random behavior of the variables are similar to their deterministic behavior.
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The main contribution is twofold: to provide some experimental insights about the behavior of the variable importance index based on random forests and to propose a strategy involving a ranking of explanatory variables using the random forests score of importance and a stepwise ascending variable introduction strategy.
Next, the data are smoothed using a moving average filter to remove sources of idiosyncratic variation that are unrelated to the cyclical behavior of the variable (the smoothing step is omitted when using quarterly data due to the coarse frequency of the data).
The effect of the A quadratic factor is significant, while the effect of the A factor is not significant because the behavior of the variable is not linear within the range studied, and the behavior of the low and high levels is not statistically different.
The figure shows that while the stochastic behaviors of the variables are similar to their deterministic and random counterparts, the volatility in the variables (R t)) and (B t)) indicates the highly random nature of these components.
Remarkably, the behavior of these variables is consistent since the larger the abundance of unsaturated carbons, the lower the number of protons contributing to the –(CH2) n – methylenes signals in acyl chains.
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