Parametric estimation of discretely observed diffusions using the EM algorithm
Papaspiliopoulos, Omiros and Sermaidis, Giorgos (2007) Parametric estimation of discretely observed diffusions using the EM algorithm. Working Paper. University of Warwick. Centre for Research in Statistical Methodology, Coventry.
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Official URL: http://www2.warwick.ac.uk/fac/sci/statistics/crism...
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|
|Number of Pages:||5|
|Status:||Not Peer Reviewed|
|Access rights to Published version:||Open Access|
|References:|| Kloeden, P. and Platen, E. (1995) Numerical Solution of Stochastic Differential Equations. New York: Springer.  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.  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.  Fearnhead, P., Papaspiliopoulos, O. and Roberts, G. O. (2006) Particle filters for partially observed diffusions. In revision.|
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