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CSDA
2008

Bayesian inference for nonlinear multivariate diffusion models observed with error

13 years 11 months ago
Bayesian inference for nonlinear multivariate diffusion models observed with error
Diffusion processes governed by stochastic differential equations (SDEs) are a well established tool for modelling continuous time data from a wide range of areas. Consequently, techniques have been developed to estimate diffusion parameters from partial and discrete observations. Likelihood based inference can be problematic as closed form transition densities are rarely available. One widely used solution
Andrew Golightly, Darren J. Wilkinson
Added 10 Dec 2010
Updated 10 Dec 2010
Type Journal
Year 2008
Where CSDA
Authors Andrew Golightly, Darren J. Wilkinson
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