Exact and computationally efficient likelihood-based estimation for discretely observed diffusion processes (with discussion)
AbstractThe 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. Copyright 2006 Royal Statistical Society.
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Bibliographic InfoArticle provided by Royal Statistical Society in its journal Journal of the Royal Statistical Society: Series B (Statistical Methodology).
Volume (Year): 68 (2006)
Issue (Month): 3 ()
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