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Computational Methods for Data Evaluation and Assimilation.

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...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Cacuci, Dan Gabriel
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Hoboken : CRC Press, 2013.
Temas:
Acceso en línea:Texto completo

MARC

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520 |a 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 experiment. 
504 |a Includes bibliographical references and index. 
505 0 |a Front Cover; Contributors; Preface; List of Figures; List of Tables; Contents; Introduction; Chapter 1 -- Experimental Data Evaluation: Basic Concepts; Chapter 2 -- Computation of Means and Variances from Measurements; Chapter 3 -- Optimization Methods For Large-Scale Data Assimilation; Chapter 4 -- Basic Principles of 4-D VAR; Chapter 5 -- 4-D VAR in Numerical Weather Prediction Models; Chapter 6 -- Appendix A; Chapter 7 -- Appendix B; Chapter 8 -- Appendix C; Bibliography; Back Cover. 
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