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Application of mean-covariance regression methods for estimation of edp|im distributions for small record sets

Ghods, B ; Sharif University of Technology | 2021

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  1. Type of Document: Article
  2. DOI: 10.1080/13632469.2021.1961938
  3. Publisher: Taylor and Francis Ltd , 2021
  4. Abstract:
  5. 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. © 2021 Taylor & Francis Group, LLC
  6. Keywords:
  7. Efficiency ; Maximum principle ; Regression analysis ; Engineering demand parameters ; Expectation-maximization method ; Floor accelerations ; Intensity measure ; Inter-story drift ratios ; Ordinary least squares ; Penalized weighted least squares ; Performance assessment ; Least squares approximations
  8. Source: Journal of Earthquake Engineering ; 2021 ; 13632469 (ISSN)
  9. URL: https://www.tandfonline.com/doi/abs/10.1080/13632469.2021.1961938?journalCode=ueqe20