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Sparse Grids and Applications

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Cover of 'Sparse Grids and Applications'

Table of Contents

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    Book Overview
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    Chapter 1 An Adaptive Sparse Grid Approach for Time Series Prediction
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    Chapter 2 Efficient Analysis of High Dimensional Data in Tensor Formats
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    Chapter 3 Sparse Grids in a Nutshell
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    Chapter 4 Intraday Foreign Exchange Rate Forecasting Using Sparse Grids
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    Chapter 5 Dimension- and Time-Adaptive Multilevel Monte Carlo Methods
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    Chapter 6 An Efficient Sparse Grid Galerkin Approach for the Numerical Valuation of Basket Options Under Kou’s Jump-Diffusion Model
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    Chapter 7 The Use of Sparse Grid Approximation for the r -Term Tensor Representation
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    Chapter 8 On Multilevel Quadrature for Elliptic Stochastic Partial Differential Equations
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    Chapter 9 Local and Dimension Adaptive Stochastic Collocation for Uncertainty Quantification
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    Chapter 10 The Combination Technique for the Initial Value Problem in Linear Gyrokinetics
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    Chapter 11 Model Reduction with the Reduced Basis Method and Sparse Grids
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    Chapter 12 Spatially Adaptive Refinement
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    Chapter 13 Asymptotic Expansion Around Principal Components and the Complexity of Dimension Adaptive Algorithms
Attention for Chapter 10: The Combination Technique for the Initial Value Problem in Linear Gyrokinetics
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Chapter title
The Combination Technique for the Initial Value Problem in Linear Gyrokinetics
Chapter number 10
Book title
Sparse Grids and Applications
Published by
Springer, Berlin, Heidelberg, January 2012
DOI 10.1007/978-3-642-31703-3_10
Book ISBNs
978-3-64-231702-6, 978-3-64-231703-3
Authors

Christoph Kowitz, Dirk Pflüger, Frank Jenko, Markus Hegland, Kowitz, Christoph, Pflüger, Dirk, Jenko, Frank, Hegland, Markus

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