Statistical procedures for developing earthquake damage fragility curves

TLDR

Fragility curves are common in earthquake engineering, yet most work focuses on data acquisition rather than on fitting procedures, and this paper synthesizes the most used fitting methods while highlighting their limitations. The study develops statistical procedures for creating earthquake damage fragility curves, including methods to handle intensity‑measure uncertainty and to select models based on prediction‑error evaluation. The authors present novel parametric approaches (generalized linear and cumulative link models) and non‑parametric techniques (generalized additive models and Gaussian kernel smoothing), discuss their advantages and disadvantages, and illustrate them with empirical and analytical data. © 2015 John Wiley & Sons, Ltd.

Abstract

Summary This paper describes statistical procedures for developing earthquake damage fragility functions. Although fragility curves abound in earthquake engineering and risk assessment literature, the focus has generally been on the methods for obtaining the damage data (i.e., the analysis of structures), and little emphasis is placed on the process for fitting fragility curves to this data. This paper provides a synthesis of the most commonly used methods for fitting fragility curves and highlights some of their significant limitations. More novel methods are described for parametric fragility curve development (generalized linear models and cumulative link models) and non‐parametric curves (generalized additive model and Gaussian kernel smoothing). An extensive discussion of the advantages and disadvantages of each method is provided, as well as examples using both empirical and analytical data. The paper further proposes methods for treating the uncertainty in intensity measure, an issue common with empirical data. Finally, the paper describes approaches for choosing among various fragility models, based on an evaluation of prediction error for a user‐defined loss function. Copyright © 2015 John Wiley & Sons, Ltd.