- Ground-motion model is:
_{1}= -1.18, a_{2}= 0.559, a_{3}= -1.624, a_{4}= 0.018, a_{5}= 0.445, a_{B}= 0.25, a_{C}= 0.31, a_{D}= 0.33, a_{N}= -0.01, a_{R}= 0.09, a_{S}= -0.05, k_{1}= 2.03, k_{2}= -0.138, k_{3}= -0.962 and σ = 0.36^{27}. - Use four Eurocode 8 classes:
- A
- Rock. S
_{B}= S_{C}= S_{D}= 0. - B
- Stiff soil. S
_{B}= 1, S_{C}= S_{D}= 0. - C
- Medium-dense soil deposits. S
_{C}= 1, S_{B}= S_{D}= 0. - D
- Soft soil deposits. S
_{D}= 1, S_{B}= S_{C}= 0.

- Use three faulting mechanisms:
- Normal
- E
_{N}= 1, E_{R}= E_{S}= 0. - Reverse
- E
_{R}= 1, E_{N}= E_{S}= 0. - Strike-slip
- E
_{S}= 1, E_{N}= E_{R}= 0.

- Update of Cauzzi and Faccioli (2008) (see Section 2.289) using more data and r
_{rup}rather than r_{hypo}because this is more appropriate close to large earthquakes. - Find that differences between r
_{rup}and r_{hypo}are not statistically significant for M_{w}≤ 5.7 so use r_{hypo}below this threshold. - Most data from Japan.
- Use a subset of data to decide on the best functional form, including forms with M
_{w}^{2}and/or distance-saturation terms and site classes or V_{s,30}directly. - Carefully examine (not show) fit between predicted and observed spectra in near-source region and find distance-saturation term provides best fit.
- Note that M
_{w}^{2}term has negligible impact on σ but improves predictions for large M_{w}. Drops M_{w}^{2}from final functional form. - Find site terms significantly reduce σ.
- Effect of style of faulting terms on σ is minimal but does improve predictions.
- Note that functional form means that one-step rather than two-step approach must be used that means that effects of magnitude and distance cannot be decoupled and σs are larger.
- Compare predictions and observations for two records and find overprediction in one case and underprediction in other, which relate to the approximation of the model and not an error in determination of coefficients.
- Test model against data (4.5 ≤ M
_{w}≤ 6.9, r_{rup}< 150km) from the Italian Accelerometric Archive (ITACA) using residual plots and method of Scherbaum et al. (2004). Find that good ranking is obtained using approach of Scherbaum et al. (2004). Find trends in residual plots, which correct using functions, with coefficients k_{1}, k_{2}and k_{3}, fit to the residuals. k_{i}can be added to a_{i}to obtain corrected coefficients (a_{4}and a_{5}are unchanged). - Note that improvements to Cauzzi and Faccioli (2008) are still ongoing.

^{27}Typographical error in article (E_{I} should be E_{S}).