ABSTRACT

The performance of several regression methods is investigated to estimate the distribution of engineering demand parameters conditioned on intensity measures (EDP|IM) for small record sets. In particular, the performance of the multivariate ordinary least squares (OLS), a simultaneous mean-variance regression (MVR) done by a penalized weighted least-square loss function, and a mean-covariance/variance regression based on expectation maximization method (EM) are assessed. The efficiency of the introduced methods is compared with FEMA-P58 methodology. Performance assessment of EM and MVR methods shows that the overall increase in efficiency is about 25–45% for maximum inter-story drift ratios, and 30–50% for maximum absolute floor acceleration.

摘要

研究了几种回归方法的性能，以估计以小型记录集的强度测量 (EDP|IM) 为条件的工程需求参数的分布。特别是多元普通最小二乘法 (OLS)、由惩罚加权最小二乘损失函数完成的同时均方差回归 (MVR) 和基于期望最大化方法 (EM) 的均值协方差/方差回归的性能) 进行评估。将所介绍方法的效率与 FEMA-P58 方法进行了比较。EM 和 MVR 方法的性能评估表明，对于最大层间漂移比，效率的总体提高约为 25-45%，对于最大绝对楼层加速度，效率总体提高了 30-50%。