This book deals with the numerical analysis and efficient numerical treatment of high-dimensional integrals using sparse grids and other dimension-wise integration techniques with applications to finance and insurance. The book focuses on providing insights into the interplay between coordinate transformations, effective dimensions and the convergence behaviour of sparse grid methods. The techniques, derivations and algorithms are illustrated by many examples, figures and code segments. Numerical experiments with applications from finance and insurance show that the approaches presented in th
Stochastic optimisation problems minimise expectations of random cost functions. Thus they require a...
The calculation of likelihood functions of many econometric models requires the evaluation of integr...
Abstract. Approximation problems in high dimensions arise in numerous applications such as problems ...
Summary. In this paper we present a locally and dimension-adaptive sparse grid method for interpolat...
AbstractWe present a new general class of methods for the computation of high-dimensional integrals....
In this work we analyze the dimension-independent convergence property of an abstract sparse quadrat...
This volume of LNCSE is a collection of the papers from the proceedings of the third workshop on spa...
The technique of sparse grids allows to overcome the curse of dimensionality, which prevents the use...
Sparse grids are constructed as logical sums of product grids. Each product grid is formed by select...
For the estimation of many econometric models, integrals without analytical solutions have to be eva...
In the recent decade, there has been growing interest in the numerical treatment of high-dimensional...
This volume of LNCSE is a collection of the papers from the proceedings of the third workshop on spa...
For the approximation of multidimensional functions, using classical numerical discretization scheme...
For the estimation of many econometric models, integrals without analytical solutions have to be eva...
I would like to thank my supervisor Dr. Reisinger for all his help, guidance and programming experti...
Stochastic optimisation problems minimise expectations of random cost functions. Thus they require a...
The calculation of likelihood functions of many econometric models requires the evaluation of integr...
Abstract. Approximation problems in high dimensions arise in numerous applications such as problems ...
Summary. In this paper we present a locally and dimension-adaptive sparse grid method for interpolat...
AbstractWe present a new general class of methods for the computation of high-dimensional integrals....
In this work we analyze the dimension-independent convergence property of an abstract sparse quadrat...
This volume of LNCSE is a collection of the papers from the proceedings of the third workshop on spa...
The technique of sparse grids allows to overcome the curse of dimensionality, which prevents the use...
Sparse grids are constructed as logical sums of product grids. Each product grid is formed by select...
For the estimation of many econometric models, integrals without analytical solutions have to be eva...
In the recent decade, there has been growing interest in the numerical treatment of high-dimensional...
This volume of LNCSE is a collection of the papers from the proceedings of the third workshop on spa...
For the approximation of multidimensional functions, using classical numerical discretization scheme...
For the estimation of many econometric models, integrals without analytical solutions have to be eva...
I would like to thank my supervisor Dr. Reisinger for all his help, guidance and programming experti...
Stochastic optimisation problems minimise expectations of random cost functions. Thus they require a...
The calculation of likelihood functions of many econometric models requires the evaluation of integr...
Abstract. Approximation problems in high dimensions arise in numerous applications such as problems ...