Extension of the Random‐Effects Regression Algorithm to Account for the Effects of Nonlinear Site Response
Extension of the Random‐Effects Regression Algorithm to Account for the Effects of Nonlinear Site Response
复制标题
随机效应回归算法的扩展以解释非线性站点响应的影响
DOI：
10.1785/0120140368
复制
发表时间：
2015
影响因子：
3
通讯作者：
P. Stafford
中科院分区：
文献类型：
--
作者：
P. Stafford
由Abrahamson和Young(1992)在工程地震学中流行起来的随机效应回归算法，可以说是建立经验地震动模型的最常用的方法。该算法最初的介绍涉及到一种更一般的混合效果模型公式的最简单应用。近年来，在经验或半经验地震动模型中引入非线性场地响应效应已变得越来越普遍，但原始的随机效应算法不适用于随机效应以非线性方式进入模型的情况。本文提出了一种更通用的算法，用于拟合能够适应非线性场地效应(以及其他效应)的混合效应模型。提出的算法有意地反映了Abrahamson和Young(1992)的算法，但允许处理更复杂的方差结构。
Abstract The random-effects regression algorithm, made popular within engineering seismology by Abrahamson and Youngs (1992), is arguably the most commonly used approach for developing empirical ground-motion models. The original presentation of this algorithm relates to the most simple application of a far more general mixed-effects model formulation. In recent years, it has become increasingly common to incorporate nonlinear site response effects within empirical, or semi-empirical, ground-motion models, but the original random-effects algorithm does not apply to cases in which the random effects enter the model in a nonlinear manner. This article presents a more general algorithm for fitting mixed-effects models that can accommodate nonlinear site effects (among other effects). The presented algorithm deliberately mirrors that of Abrahamson and Youngs (1992) but allows for the treatment of far more elaborate variance structures.