  New global sensitivity measures based on quantiles of the output are
introduced. Such measures can be used for global sensitivity analysis of
problems in which quantiles are explicitly the functions of interest and for
identification of variables which are the most important in achieving extreme
values of the model output. It is proven that there is a link between
introduced measures and Sobol main effect sensitivity indices. Two different
Monte Carlo estimators are considered. It is shown that the double loop
reordering approach is much more efficient than the brute force estimator.
Several test cases and practical case studies related to structural safety are
used to illustrate the developed method. Results of numerical calculations show
the efficiency of the presented technique.
