Advances in High-Order Sensitivity by Dan Gabriel Cacuci (.PDF)
File Size: 12 MB
Advances in High-Order Sensitivity Analysis (Advances in Applied Mathematics) by Dan Gabriel Cacuci
Requirements: .PDF reader, 12 MB
Overview: 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’s 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.
Genre: Non-Fiction > Educational > Applied Mathematics
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