Deriving Empirical Ground-Motion Models: Balancing Data Constraints and Physical Assumptions to Optimize Prediction Capability

2009 ◽  
Vol 99 (4) ◽  
pp. 2335-2347 ◽  
Author(s):  
N. M. Kuehn ◽  
F. Scherbaum ◽  
C. Riggelsen
Keyword(s):  
Ground Motion ◽  
Motion Models ◽  
Empirical Ground ◽  
Ground Motion Models ◽  
Data Constraints ◽  
Prediction Capability

A Bayesian model for truncated regression for the estimation of empirical ground-motion models

2020 ◽  
Vol 18 (14) ◽  
pp. 6149-6179
Author(s):  
Nicolas Martin Kuehn ◽  
Tadahiro Kishida ◽  
Mohammad AlHamaydeh ◽  
Grigorios Lavrentiadis ◽  
Yousef Bozorgnia
Keyword(s):  
Ground Motion ◽  
Bayesian Model ◽  
Truncated Regression ◽  
Motion Models ◽  
Empirical Ground ◽  
Ground Motion Models

scholarly journals A Primer for using INLA to Estimate Ground-Motion Models

2021 ◽  
Author(s):  
Nicolas Kuehn
Keyword(s):  
Ground Motion ◽  
R Package ◽  
Motion Models ◽  
Empirical Ground ◽  
Ground Motion Models

This document provides a brief introduction int the use of the R package R-INLA for the development of empirical ground-motion models.

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