Likelihood inference for discretely observed non-linear diffusions.
This paper is concerned with the Bayesian estimation of nonlinear stochastic differential equations when observations are discretely sampled. The estimation framework relies on the introduction of latent auxiliary data to complete the missing diffusion between each pair of measurements. Tuned Markov...
| Main Authors: | , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
Econometric Society
2001
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