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Global Prior Sensitivity in Regression Coefficients Estimation
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Explore Laplacian prior impact on regression coefficients and observation noise in spatial precisions analysis. Figure visualizations included.
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Global Prior Sensitivity in Regression Coefficients Estimation
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Presentation Transcript
q1 q2 a b u1 u2 l W A Y Figure 1 Global prior in SPM2: Laplacian prior: Y=XW+E [TxN] [TxK] [KxN] [TxN]
Figure 2 y t x
-1 -1 -1 4 -1 Figure 3 1 -8 2 2 20 1 1 -8 -8 2 -8 2 1
Regression coefficients AR coefficients Observation noise Spatial precisions
Figure 5 y y x x
Figure 6 F Iteration Number
Figure 7 (b) (a) (d) (c)
Figure 8 Sensitivity 1-Specificity
Figure 10 (a) (b) (c) (d)
Figure 11 (b) (a) (d) (d) (c)
(b) (a) (c) (d) Figure 12
Figure 13 (a) (b) (c) (d)
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