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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