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Global Prior Sensitivity in Regression Coefficients Estimation

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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  1. 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]

  2. Figure 2 y t x

  3. -1 -1 -1 4 -1 Figure 3 1 -8 2 2 20 1 1 -8 -8 2 -8 2 1

  4. Regression coefficients AR coefficients Observation noise Spatial precisions

  5. Figure 5 y y x x

  6. Figure 6 F Iteration Number

  7. Figure 7 (b) (a) (d) (c)

  8. Figure 8 Sensitivity 1-Specificity

  9. Figure 9

  10. Figure 10 (a) (b) (c) (d)

  11. Figure 11 (b) (a) (d) (d) (c)

  12. (b) (a) (c) (d) Figure 12

  13. Figure 13 (a) (b) (c) (d)

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