Sebastian Reich is Professor of Numerical Analysis at the University of Potsdam (full time) and the University of Reading (part time). He also holds an honorary visiting professorship at Imperial College London. Reich is the author of over 100 journal articles and the co-author of Simulating Hamiltonian Dynamics (Cambridge, 2005), which has received more than 600 citations. His research areas cover numerical analysis and scientific computing with applications to classical mechanics, molecular dynamics, geophysical fluid dynamics, and data assimilation. In 2003 he received the Germund Dahlquist Prize from the Society for Industrial and Applied Mathematics (SIAM) for his work on geometric integration methods.
Inhaltsangabe
Preface 1. Prologue: how to produce forecasts Part I. Quantifying Uncertainty: 2. Introduction to probability 3. Computational statistics 4. Stochastic processes 5. Bayesian inference Part II. Bayesian Data Assimilation: 6. Basic data assimilation algorithms 7. McKean approach to data assimilation 8. Data assimilation for spatio-temporal processes 9. Dealing with imperfect models References Index.
Preface 1. Prologue: how to produce forecasts Part I. Quantifying Uncertainty: 2. Introduction to probability 3. Computational statistics 4. Stochastic processes 5. Bayesian inference Part II. Bayesian Data Assimilation: 6. Basic data assimilation algorithms 7. McKean approach to data assimilation 8. Data assimilation for spatio-temporal processes 9. Dealing with imperfect models References Index.
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