The slip of each sub-fault is estimated using the non-negative least square method, and its corresponding error is calculated using the jackknife method (Fujii and Satake 2006, 2007).
Table 2 lists the average errors between predicted and actual MLI and average errors of the absolute value in our model using the jackknife method and Mito et al.'s method (MM).
The network was trained and tested using the jackknife method and its performance was then compared with that of the radiologists in terms of sensitivity, specificity and accuracy using receiver operating characteristic curve (ROC) analysis.
Country-level fixed effects were included to absorb unobserved country-level heterogeneity (e.g., determinants of variation in case fatality rates not explained by other covariates in the model), and robust standard errors, clustered by country, were estimated using the jackknife method.
To assess possible latency effects, an additional 10 Hz low-pass filter was applied to reduce noise (and thus increase robustness) and the time at which the corrected difference waves reached −0.6 µV, starting at 140 ms post-target onset, was measured using the jackknife method [48] [50].
Confidence intervals were derived using the jackknife method.
