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Sparse Grids and Applications

Overview of attention for book
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 1: An Adaptive Sparse Grid Approach for Time Series Prediction
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Citations

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Chapter title
An Adaptive Sparse Grid Approach for Time Series Prediction
Chapter number 1
Book title
Sparse Grids and Applications
Published by
Springer, Berlin, Heidelberg, January 2012
DOI 10.1007/978-3-642-31703-3_1
Book ISBNs
978-3-64-231702-6, 978-3-64-231703-3
Authors

Bastian Bohn, Michael Griebel, Bohn, Bastian, Griebel, Michael

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 2 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 50%
Unknown 1 50%

Demographic breakdown

Readers by professional status Count As %
Professor 1 50%
Student > Ph. D. Student 1 50%
Readers by discipline Count As %
Mathematics 1 50%
Computer Science 1 50%

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