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Table 1 Optimal hyper-parameters for each case

From: Joint inversion of strain and tilt data using the Akaike’s Bayesian information criterion to map detailed slip distributions of short-term slow slip events

Case ABIC \({\alpha }^{2}\) \({\sigma }_{1}^{2}\) \({\eta }^{2}\)(strain/tilt)
Synthetic data − 445.38 4.16 × 10–15 5.08 × 10–20 0.92
Example 1: 14–19 April 2015 2.45 1.26 × 10–10 1.80 × 10–15 0.38
 Based on stain data alone 229.32 3.40 × 10–12 1.01 × 10–16
 Based on tilt data alone 420.14 8.11 × 10–11 2.16 × 10–15
Example 2: 29 December 2015 to 1 January 2016 − 336.63 4.35 × 10–11 6.23 × 10–17 0.10
Example 2: 1–5 January 2016 − 284.53 1.64 × 10–11 2.20 × 10–16 0.25
Example 2: 5–7 January 2016 − 320.50 4.81 × 10–11 1.10 × 10–16 0.91
Example 3: 23–27 October 2016 547.83 6.85 × 10–11 8.01 × 10–16 0.46
 Based on stain data alone*1 780.51 8.74 × 10–10 1.33 × 10–15
 Based on tilt data alone*1 702.08 1.82 × 10–11 5.73 × 10–16