Exact and computationally efficient likelihood-based estimation for discretely observed diffusion processes (with discussion)

Authors


Gareth O. Roberts, Department of Mathematics and Statistics, Fylde College, Lancaster University, Lancaster, LA1 4YF, UK.
E-mail: g.o.roberts@lancaster.ac.uk

Abstract

Summary.  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.

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