The high-order sensitivities of model responses with respect to model parameters are notoriously difficult to compute for large-scale models involving many parameters. The neglect of higher-order response sensitivities leads to substantial errors in predicting the moments (expectation, variance, skewness, kurtosis, and higher-order) of the model response\u2019s distribution in the phase space of model parameters. The author expands on his theory of addressing high-order sensitivity analysis in this book, Advances in High-Order Sensitivity Analysis.\nThe mathematical/computational models of physical systems comprise parameters, independent variables, and dependent variables. Since the physical processes themselves are seldom known precisely and since most of the model\u2019s parameters stem from\n\nAdvances in High-Order Sensitivity Analysis\n\nFree UK delivery on this item.\n\nThis brand new item is available with free UK delivery using Royal Mail tracked services.\n\nPlease note: th;