A Monte Carlo method for simulating a multi-dimensional diffusion process conditioned on hitting a fixed point at a fixed future time is developed. Proposals for such diffusion bridges are obtained by superimposing an additional guiding term to the drift of the process under consideration. The guiding term is derived via approximation of the target process by a simpler diffusion processes with known transition densities. Acceptance of a proposal can be determined by computing the likelihood ratio between the proposal and the target bridge, which is derived in closed form.We show under general conditions that the likelihood ratio is well defined and show that a class of proposals with guiding term obtained from linear approximations fall und...
We consider the task of generating discrete-time realisations of a nonlinear multivariate diffusion ...
Abstract. We propose a method for estimating first passage time densities of one-dimensional diffusi...
This article develops a class of Monte Carlo (MC) methods for simulating conditioned diffusion samp...
A Monte Carlo method for simulating a multi-dimensional diffusion process conditioned on hitting a f...
We propose simple methods for multivariate diffusion bridge simulation, which plays a fundamental ro...
With a view to likelihood inference for discretely observed diffusion type models, we propose a simp...
Revised with new numerical examplesWe consider the problem of simulating diffusion bridges, which ar...
simulation of diffusion bridges with application to likelihood inference for diffusion
Estimation of parameters of a diffusion based on discrete time observations poses a difficult proble...
Multilevel Monte Carlo is a novel method for reducing the computational cost when computing conditio...
Diffusion processes are widely used in engineering, finance, physics, and other fields. Usually cont...
Diffusion processes are widely used in engineering, fiance, physics and other fields. Usually contin...
This work consists of two separate parts. In the first part we extend the work on exact simulation o...
We introduce a Multilevel Monte Carlo method for approximating the transitiondensity for discretely ...
This article makes two contributions. First, we outline a simple simulation-based framework for cons...
We consider the task of generating discrete-time realisations of a nonlinear multivariate diffusion ...
Abstract. We propose a method for estimating first passage time densities of one-dimensional diffusi...
This article develops a class of Monte Carlo (MC) methods for simulating conditioned diffusion samp...
A Monte Carlo method for simulating a multi-dimensional diffusion process conditioned on hitting a f...
We propose simple methods for multivariate diffusion bridge simulation, which plays a fundamental ro...
With a view to likelihood inference for discretely observed diffusion type models, we propose a simp...
Revised with new numerical examplesWe consider the problem of simulating diffusion bridges, which ar...
simulation of diffusion bridges with application to likelihood inference for diffusion
Estimation of parameters of a diffusion based on discrete time observations poses a difficult proble...
Multilevel Monte Carlo is a novel method for reducing the computational cost when computing conditio...
Diffusion processes are widely used in engineering, finance, physics, and other fields. Usually cont...
Diffusion processes are widely used in engineering, fiance, physics and other fields. Usually contin...
This work consists of two separate parts. In the first part we extend the work on exact simulation o...
We introduce a Multilevel Monte Carlo method for approximating the transitiondensity for discretely ...
This article makes two contributions. First, we outline a simple simulation-based framework for cons...
We consider the task of generating discrete-time realisations of a nonlinear multivariate diffusion ...
Abstract. We propose a method for estimating first passage time densities of one-dimensional diffusi...
This article develops a class of Monte Carlo (MC) methods for simulating conditioned diffusion samp...