English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

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.

Application of Mean-covariance Regression Methods for Estimation of EDP|IM Distributions for Small Record Sets