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. Copyright 2006 Royal Statistical Society.

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Year of publication:	2006
Authors:	Beskos, Alexandros ; Papaspiliopoulos, Omiros ; Roberts, Gareth O. ; Fearnhead, Paul
Published in:	Journal of the Royal Statistical Society Series B. - Royal Statistical Society - RSS, ISSN 1369-7412. - Vol. 68.2006, 3, p. 333-382
Publisher:	Royal Statistical Society - RSS

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Extent:	text/html
Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://ebvufind01.dmz1.zbw.eu/10005140170