## 3 Results
### Peak Rotation and Translation Scaling Relations  
The scaling relation for peak rotation and peak translation was analyzed for the set containing all data (IMI + PLA) and separated data sets (Figure 6). Moreover, two models were evaluated for each data set, i.e., linear function without intercept (Figure 6a,c) and linear function with intercept (Figure 6b,d). Statistical assessment was performed by applying the determination coefficient (R2) and the standard error of estimate (SEE). The fitting procedure was the orthogonal distance regression method. Assuming that the estimation of the HVSR and TRSR curves and peak values of the rotational and translational  
Figure 5: HVSR and TRSR curves of 70 events from the PLA station: **(a)** Average HVSR for translational acceleration and theoretical amplification model (green line); **(b)** HVSR in EW direction for translational acceleration; **(c)** HVSR in NS direction for translational acceleration; **(d)** Average TRSR rotational velocity; **(e)** TRSR in EW direction for rotational velocity; **(f)** TRSR in NS direction for rotational velocity. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{3}{*}{
\begin{tabular}{c} **Type of** \\ **Motion** \\ \end{tabular} } & \multirow{3}{*}{**Component**} & \multicolumn{3}{c}{**IMI Station**} & \multicolumn{3}{c}{**PLA Station**} \\ \cline{3-8}  & & \multicolumn{2}{c}{**Maximum I**} & \multicolumn{2}{c}{**Maximum II**} & \multicolumn{2}{c}{**Maximum**} \\ \cline{3-8}  & \multirow{2}{*}{**\(\mathbf{f_{0}}\) [Hz]**} & \multicolumn{2}{c}{**Amplification**} & \multirow{2}{*}{**\(\mathbf{f_{0}}\) [Hz]**} & \multicolumn{2}{c}{**Amplification**} & \multirow{2}{*}{**\(\mathbf{f_{0}}\) [Hz]**} & \multicolumn{2}{c}{**Amplification**} \\  & & & **Peak Value** & & & **Peak Value** & \\ \hline \multirow{3}{*}{Translation} & AV HVSR & \multirow{3}{*}{1.6} & \multirow{3}{*}{6.8} & \multirow{3}{*}{2.2} & \multirow{3}{*}{3.9} & \multirow{3}{*}{4.2} & \multirow{3}{*}{4.7} \\  & PGA & & & & & & \\ \cline{1-1} \cline{2-8}  & EW PGA & 1.6 & 6.7 & 2.4 & 3.4 & 5.8 & 4.3 \\ \cline{1-1} \cline{2-8}  & NS PGA & 1.4 & 7.1 & 2.2 & 4.1 & 4.2 & 5.6 \\ \hline \multirow{3}{*}{Rotation} & AV TRSR & \multirow{3}{*}{1.8} & \multirow{3}{*}{2.5} & \multirow{3}{*}{4.4} & \multirow{3}{*}{1.6} & \multirow{3}{*}{5.6} & \multirow{3}{*}{1.9} \\  & PRV & & & & & & \\ \cline{1-1} \cline{2-8}  & EW PRV & 1.8 & 3.1 & 4.6 & 1.7 & 5.8 & 2.7 \\ \cline{1-1} \cline{2-8}  & NS PRV & 1.8 & 3.7 & 4.4 & 1.7 & 5.4 & 1.8 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Resonance frequencies and amplification factors were obtained for rotation and translation in each component: average, EW (x-axis), and NS (y-axis). signals were found for the same type of body wave, the peak values were divided by the empirical amplification coefficients for the S-wave. Therefore, all calculations were conducted twice, first for the data sets with raw peak values and the second for data sets divided by the appropriate amplification coefficient. The estimation results assuming the orthogonal distance regression method are shown in Table 4. Twelve linear models were considered, and eight showed the determination coefficient R2 \(>\) 0.90. This simple parameter indicated that the linear models without an intercept generally fit better than those with an intercept \(b\). Moreover, it is noticeable that the correction procedure produced higher values of slope \(a\) than the raw data points in each case. In the case of the entire model, the slope increased from 4.07 \(\times\) 10\({}^{-4}\) to 9.37 \(\times\) 10\({}^{-4}\), while for the model without the intercept, the values changed from 4.62 \(\times\) 10\({}^{-4}\) to 1.29 \(\times\) 10\({}^{-3}\). An opposite situation can be noticed for the \(b\)-parameter, which decreased from 5.1 \(\times\) 10\({}^{-6}\) to 1.79 \(\times\) 10\({}^{-6}\) after data correction. The separate models for the IMI and PLA stations presented similar behavior.