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

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  • Alexandros Beskos
  • Omiros Papaspiliopoulos
  • Gareth O. Roberts
  • Paul Fearnhead

Abstract

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.

Suggested Citation

  • Alexandros Beskos & Omiros Papaspiliopoulos & Gareth O. Roberts & Paul Fearnhead, 2006. "Exact and computationally efficient likelihood-based estimation for discretely observed diffusion processes (with discussion)," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 68(3), pages 333-382.
  • Handle: RePEc:bla:jorssb:v:68:y:2006:i:3:p:333-382
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