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It is well known that likelihood inference for arbitrary nonlinear diffusion processes observed at discrete times is problematic since closed form transition densities are rarely tractable. One widely used solution involves the introduction of latent data points between every pair of observations to ...

As post-genomic biology becomes more predictive, the ability to infer rate parameters (known as reverse-engineering) of biochemical networks will become increasingly important. One approach is to replace the underlying model by a diffusion approximation and the model is identified using discrete-tim ...