Data evaluation and data combination require the use of a wide range of probability theory concepts and tools, from deductive statistics mainly concerning frequencies and sample tallies to inductive inference for assimilating non-frequency data and a priori knowledge. Computational Methods for Data Evaluation and Assimilation presents interdisciplinary methods for integrating experimental and computational information. This self-contained book shows how the methods can be applied in many scientific and engineering areas.
After presenting the fundamentals underlying the evaluation of experimental data, the book explains how to estimate covariances and confidence intervals from experimental data. It then describes algorithms for both unconstrained and constrained minimization of large-scale systems, such as time-dependent variational data assimilation in weather prediction and similar applications in the geophysical sciences. The book also discusses several basic principles of four-dimensional variational assimilation (4D VAR) and highlights specific difficulties in applying 4D VAR to large-scale operational numerical weather prediction models.
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"This book, addressed to graduate students, post-graduate students, and inter-disciplinary scientist, focuses on computational techniques used to experimental data evaluation and assimilation. The theory is illustrated with examples belonging to many scientific and engineering domains."
―Florin Gorunescu, in Zentralblatt MATH 1283
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Book Description Hardcover. Condition: New. Seller Inventory # 6666-TNFPD-9781584887355
Book Description Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Cacuci, Dan Gabriel Navon, Ionel Michael Ionescu-Bujor, MihaelaData evaluation and data combination require the use of a wide range of probability theory concepts and tools, from deductive statistics mainly concerning frequencies and sample tal. Seller Inventory # 869727889
Book Description Hardcover. Condition: Brand New. 1st edition. 480 pages. 9.49x6.14x1.02 inches. In Stock. This item is printed on demand. Seller Inventory # __1584887354
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