| \(\alpha _{opt}\) | \(q_{\text {max}}\) | \(\rho\) | pval | \(FDR<0.05\) |
---|
\(m=1000\) | 10 | 2 | 0.86 | \(1.3\cdot 10^{-277}\) | \(95.2\%\) |
\(m=800\) | 10 | 3 | 0.82 | \(3.0\cdot 10^{-180}\) | \(93.4\%\) |
\(m=500\) | 10 | 3 | 0.78 | \(2.0\cdot 10^{-94}\) | \(91.0\%\) |
\(m=200\) | 10 | 6 | 0.78 | \(3.5\cdot 10^{-38}\) | \(90.0\%\) |
- Number of time samples (\(n = 6\)) and noise amplitude (\(C=0.2\)) are kept fixed. Legend—\(\alpha _{opt}\): optimal value of the regularization parameter; \(q_{\text {max}}\): error threshold expressed as percentile of the MSE distribution; \(\rho\): Pearson correlation coefficient; pval: p value; FDR: false discovery rate. For each instance of the noise distribution considered, we found a negligible variability of the quality indices, therefore variance is not reported in the table