Papaspiliopoulos, Omiros and Sermaidis, Giorgos (2007) Parametric estimation of discretely observed diffusions using the EM algorithm. Working Paper. Coventry: University of Warwick. Centre for Research in Statistical Methodology. (Working papers).

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Abstract

In this paper we report ongoing work on parametric estimation for diffusions using Monte Carlo EM algorithms. The work presented here has already been extended to high dimensional problems and models with observation errors.

Item Type:	Working or Discussion Paper (Working Paper)
Subjects:	Q Science > QA Mathematics
Divisions:	Faculty of Science > Statistics
Library of Congress Subject Headings (LCSH):	Diffusion processes, Parameter estimation, Monte Carlo method
Series Name:	Working papers
Publisher:	University of Warwick. Centre for Research in Statistical Methodology
Place of Publication:	Coventry
Date:	2007
Volume:	Vol.2007
Number:	No.21
Number of Pages:	5
Status:	Not Peer Reviewed
Access rights to Published version:	Open Access
References:	[1] Kloeden, P. and Platen, E. (1995) Numerical Solution of Stochastic Differential Equations. New York: Springer. [2] Dempster, A. P., Laird, N. M. and Rubin, D. B. (1997) Maximum likelihood from incomplete data via the em algorithm (with discussion). J. R. Statist. Soc. B, 39, 1–38. [3] Beskos, A., Papaspiliopoulos, O., Roberts, G. O. and Fearnhead, P. (2006) Exact and computationally efficient likelihood-based estimation for discretely observed diffusion processes. J. R. Stat. Soc. Ser. B Stat. Methodol., 68, 333–382. [4] Fearnhead, P., Papaspiliopoulos, O. and Roberts, G. O. (2006) Particle filters for partially observed diffusions. In revision.
URI:	http://wrap.warwick.ac.uk/id/eprint/35556

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