WEAK CONVERGENCE OF A NUMERICAL SCHEME FOR STOCHASTIC DIFFERENTIAL EQUATIONSIn this paper a numerical scheme approximating the solution to a stochastic differential equation is presented. On bounded subsets of time, this scheme has a finite state space, which allows us to decrease the round-off error when the algorithm is implemented. At the same time, the scheme introduced turns out locally consistent for any step size of time. Weak convergence of the scheme to the solution of the stochastic differential equation is shown. WEAK CONVERGENCE OF A NUMERICAL SCHEME FOR STOCHASTIC DIFFERENTIAL EQUATIONSIn this paper a numerical scheme approximating the solution to a stochastic differential equation is presented. On bounded sub...
In this book we analyze the error caused by numerical schemes for the approximation of semilinear st...
The thesis consists of four papers on numerical complexityanalysis of weak approximation of ordinary...
This paper establishes a discretization scheme for a large class of stochastic differential equatio...
AbstractWeak local linear (WLL) discretizations are playing an increasing role in the construction o...
This paper considers numerical stability and convergence of weak schemes solving stochastic differen...
AbstractThis paper considers numerical stability and convergence of weak schemes solving stochastic ...
Models based on SDEs have applications in many disciplines, but in pratical applications calculating...
This thesis explains the theoretical background of stochastic differential equations in one dimensio...
In this thesis, the convergence analysis of a class of weak approximations of solutions of stochasti...
AbstractA convergence theorem for the continuous weak approximation of the solution of stochastic di...
Abstract. We propose a new approach to constructing weak numerical methods for nding solutions to st...
The paper considers numerical stability and convergence of weak schemes solving stochastic different...
Weak approximations have been developed to calculate the value of func-tionals of stochastic differe...
Abstract. Convergence rates of adaptive algorithms for weak approximations of Ito ̂ stochastic diffe...
We present an abstract framework for analyzing the weak error of fully discrete approximation scheme...
In this book we analyze the error caused by numerical schemes for the approximation of semilinear st...
The thesis consists of four papers on numerical complexityanalysis of weak approximation of ordinary...
This paper establishes a discretization scheme for a large class of stochastic differential equatio...
AbstractWeak local linear (WLL) discretizations are playing an increasing role in the construction o...
This paper considers numerical stability and convergence of weak schemes solving stochastic differen...
AbstractThis paper considers numerical stability and convergence of weak schemes solving stochastic ...
Models based on SDEs have applications in many disciplines, but in pratical applications calculating...
This thesis explains the theoretical background of stochastic differential equations in one dimensio...
In this thesis, the convergence analysis of a class of weak approximations of solutions of stochasti...
AbstractA convergence theorem for the continuous weak approximation of the solution of stochastic di...
Abstract. We propose a new approach to constructing weak numerical methods for nding solutions to st...
The paper considers numerical stability and convergence of weak schemes solving stochastic different...
Weak approximations have been developed to calculate the value of func-tionals of stochastic differe...
Abstract. Convergence rates of adaptive algorithms for weak approximations of Ito ̂ stochastic diffe...
We present an abstract framework for analyzing the weak error of fully discrete approximation scheme...
In this book we analyze the error caused by numerical schemes for the approximation of semilinear st...
The thesis consists of four papers on numerical complexityanalysis of weak approximation of ordinary...
This paper establishes a discretization scheme for a large class of stochastic differential equatio...