Uncertainty quantification. Theory, implementation, and applications (Q2872960)

The field of uncertainty quantification becomes an important part of the engineering of these days. It is a mixture of ideas synthesizing statistics, probability, model development, mathematical and numerical analysis, large scale computing, experimental design and experiments themselves, etc.NEWLINENEWLINEThe presented book fully reflects it. On one hand the reader will find basics of probability, statistics, random processes and Bayesian techniques suitable for parameter estimation, among others. On the other hand the author concisely describes many important, and quite complicated models as those for weather forecast, climate models, subsurface hydrology and geology models on one hand, and stochastic and numerical methods suitable for their solution. In my eyes there is a big gap between the basic tools to be used and complex models where they should be used.NEWLINENEWLINEFinally, big attention is devoted to the uncertainty propagation in models, space grid quadrature and interpolation techniques, surrogate models, prediction in the presence of model discrepancy, etc. Both local and global sensitivity analysis are, at least partially, covered in the book.NEWLINENEWLINEThe book itself is not an easy reading. On the one hand the basics are really basics, at least for a person from the field. On the other hand the models discussed in the book are typically very complicated and not easy ones as, e.g., those on weather forecast which serve the author as the prototype of this type of problems.