Surrogates av Robert B. Gramacy

529,-

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<P>Surrogates: a graduate textbook, or professional handbook, on topics at the interface between machine learning, spatial statistics, computer simulation, meta-modeling (i.e., emulation), design of experiments, and optimization. Experimentation through simulation, "human out-of-the-loop" statistical support (focusing on the science), management of dynamic processes, online and real-time analysis, automation, and practical application are at the forefront. </P><P></P><P>Topics include:</P><P></P><UL><P><LI>Gaussian process (GP) regression for flexible nonparametric and nonlinear modeling.</LI><P></P><P><LI>Applications to uncertainty quantification, sensitivity analysis, calibration of computer models to field data, sequential design/active learning and (blackbox/Bayesian) optimization under uncertainty. </LI><P></P><P><LI>Advanced topics include treed partitioning, local GP approximation, modeling of simulation experiments (e.g., agent-based models) with coupled nonlinear mean and var