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Active Subspace Methods in Theory and Practice: Applications to Kriging Surfaces

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Academic year: 2021

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Figure

Fig. 1 . The function f ( x 1 , x 2 ) = exp(0 . 7 x 1 + 0 . 3 x 2 ) varies strongest along the direction [0
Fig. 2 . The left figure shows the components of the first eigenvector from the active subspace analysis for both long ( β = 1) and short ( β = 0
Figure 3 shows the one-dimensional projections. In all subfigures, the solid black line is the mean kriging prediction, and the gray shaded region is the  two-standard-deviation confidence interval
Figure 5 shows histograms of the log of the relative error in the testing data for the two correlation lengths on both the one- and two-dimensional subspace  approxima-tions
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