Simulation of multivariate diffusion bridges

Simulation of multivariate diffusion bridges

We propose simple methods for multivariate diffusion bridge simulation, which plays a fundamental role in simulation-based likelihood and Bayesian inference for stochastic differential equations. By a novel application of classical coupling methods, the new approach generalizes a previously proposed simulation method for one-dimensional bridges to the multi-variate setting. First a method of si...

Mcmc Methods for Diffusion Bridges

We present and study a Langevin MCMC approach for sampling nonlinear diffusion bridges. The method is based on recent theory concerning stochastic partial differential equations (SPDEs) reversible with respect to the target bridge, derived by applying the Langevin idea on the bridge pathspace. In the process, a Random-Walk Metropolis algorithm and an Independence Sampler are also obtained. The ...

Simple simulation of diffusion bridges with application to likelihood inference for diffusions

With a view to likelihood inference for discretely observed diffusion type models, we propose a simple method of simulating approximations to diffusion bridges. The method is applicable to all one-dimensional diffusion processes and has the advantage that simple simulation methods like the Euler scheme can be applied to bridge simulation. Another advantage over other bridge simulation methods i...

Applied Probability Trust (3 February 2013) EXACT SIMULATION FOR DIFFUSION BRIDGES – AN ADAP- TIVE APPROACH

Exact simulation approaches for a class of diffusion bridges have recently been proposed based on rejection sampling techniques. The existing rejection sampling methods may not be practical due to small acceptance probabilities. This paper proposes an adaptive approach which improves the existing methods significantly under certain scenarios. The idea of the new method is based on a layered pro...

Multivariate Statistical Simulation