Exact and computationally efficient likelihood-based estimation for discretely observed diffusion processes (with discussion)
The objective of the paper is to present a novel methodology for likelihood-based inference for discretely observed diffusions. We propose Monte Carlo methods, which build on recent advances on the exact simulation of diffusions, for performing maximum likelihood and Bayesian estimation.
Document Type: Research Article
Affiliations: Lancaster University, UK
Publication date: June 1, 2006