# Expanding Moment Magnitude Pools for Earthquake Magnitude Homogenization
## 3 Results
### Indonesia

Table 3: Hypothesis testing results against a M\({}_{\rm W}\) pool from GCMT, ISC-GEM, and EVBIB for the Indonesian catalog. Significance level \(\alpha\) = 0.05. \(t\)-test results when either M\({}_{W,\text{GCMT-related}}\) or M\({}_{W,\text{GCMT-hypothesis}}\) are used. This implies that M\({}_{\text{S,NEIC}}\) and M\({}_{\text{S20,NEIC}}\) datasets can be combined to perform magnitude homogenization, a related topic mentioned in a previous study [3]. Hypothesis testing was also conducted on regression parameters across moment magnitude pools. For M\({}_{\text{S,ISC}}\) regression parameters, only results from M\({}_{W,\text{GCMT}}\) and M\({}_{W,\text{GCMT-hypothesis}}\) showed a significant difference with \(t\)(7720,0.05) = 1.960, \(p\) = 0.002 for the slope and \(p\) = 0.003 for the intercept. For M\({}_{\text{S,NEIC}}\) and M\({}_{\text{SZ,NEIC}}\) regression parameters, hypothesis testing found no significant differences across moment magnitude pools. Hypothesis testing was not conducted on regression parameters from M\({}_{\text{S20,NEIC}}\). Figure 4a-d show M\({}_{W,\text{GCMT-related}}\) against M\({}_{\text{S,ISC}}\), M\({}_{\text{S,NEIC}}\), M\({}_{\text{S20,NEIC}}\), and M\({}_{\text{SZ,NEIC}}\), respectively. Additionally shown in the figures are the data from M\({}_{W,\text{GCMT}}\) for comparison. As suggested from the aforementioned regressions results, there are very few differences between the datasets. Figure 5 also shows similar results for M\({}_{W,\text{GCMT-hypothesis}}\) against M\({}_{\text{S,ISC}}\), M\({}_{\text{S,NEIC}}\), and M\({}_{\text{SZ,NEIC}}\). Note that all resultant regressions appear similar to each other. The resultant magnitude homogenization regressions for all body wave magnitude types considered herein, i.e., m\({}_{\text{b,ISC}}\), m\({}_{\text{b,NEIC}}\), m\({}_{\text{b,DJA}}\), are shown in Table 5. There were significantly more data points for regression across the board and increasing \(\sigma\) as the moment magnitude pool went from M\({}_{W,\text{GCMT}}\) to M\({}_{W,\text{GCMT-hypothesis}}\). \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Magnitude** & **Pool** & **Slope, \(\beta_{1}\)** & **Intercept, \(\beta_{0}\)** & **Correlation, R2** & **Standard** & **Number of Data** \\
**Type** & & & & & **Deviation, \(\sigma\)** & **Pairs** \\ \hline M\({}_{\text{S,ISC}}\) & M\({}_{W,\text{GCMT}}\) & 0.644 & 2.282 & 0.873 & 0.181 & 3820 \\ M\({}_{W,\text{GCMT-related}}\) & 0.651 & 2.249 & 0.878 & 0.184 & 3873 \\ M\({}_{W,\text{GCMT-hypothesis}}\) & 0.661 & 2.202 & 0.887 & 0.185 & 3904 \\ \hline M\({}_{\text{S,NEIC}}\) & M\({}_{W,\text{GCMT}}\) & 0.737 & 1.753 & 0.886 & 0.190 & 1268 \\ M\({}_{W,\text{GCMT-related}}\) & 0.735 & 1.763 & 0.887 & 0.190 & 1291 \\ M\({}_{W,\text{GCMT-hypothesis}}\) & 0.736 & 1.758 & 0.889 & 0.190 & 1295 \\ \hline M\({}_{\text{S20,NEIC}}\) & M\({}_{W,\text{GCMT}}\)\({}^{1}\) & 0.737 & 1.737 & 0.877 & 0.163 & 200 \\ M\({}_{W,\text{GCMT-related}}\) & 1 & 0.737 & 1.737 & 0.877 & 0.163 & 200 \\ M\({}_{W,\text{GCMT-hypothesis}}\) & 0.737 & 1.737 & 0.877 & 0.163 & 200 \\ \hline M\({}_{\text{SZ,NEIC}}\) & M\({}_{W,\text{GCMT}}\) & 0.695 & 2.019 & 0.896 & 0.166 & 707 \\ M\({}_{W,\text{GCMT-related}}\) & 0.694 & 2.023 & 0.895 & 0.166 & 714 \\ M\({}_{W,\text{GCMT-hypothesis}}\) & 0.694 & 2.024 & 0.895 & 0.166 & 714 \\ \hline \hline \end{tabular} \({}^{1}\) Pool of M\({}_{W}\) data did not change for the corresponding magnitude type.  
\end{table} 
Table 4: Magnitude homogenization regression results from all moment magnitude pools for surface wave magnitude types.