Advanced Search
MyIDEAS: Login to save this paper or follow this series

Likelihood inference for discretely observed non-linear diffusions


Author Info

  • Neil Shephard
  • Ola Elerian
  • Siddhartha Chib


This paper is concerned with the Bayesian estimation of non-linear stochastic differential equations when only discrete observations are available. The estimation is carried out using a tuned MCMC method, in particular a blocked Metropolis-Hastings algorithm, by introducing auxiliary points and using the Euler-Maruyama discretisation scheme. Techniques for computing the likelihood function, the marginal likelihood and diagnostic measures (all based on the MCMC output) are presented. Examples using simulated and real data are presented and discussed in detail.

Download Info

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
File URL:
Download Restriction: no

Bibliographic Info

Paper provided by University of Oxford, Department of Economics in its series Economics Series Working Papers with number 1998-W10.

as in new window
Date of creation: 01 Aug 1998
Date of revision:
Handle: RePEc:oxf:wpaper:1998-w10

Contact details of provider:
Postal: Manor Rd. Building, Oxford, OX1 3UQ
Web page:
More information through EDIRC

Related research

Keywords: Bayes estimation; nonlinear diffusion; Euler-Maruyama approximation; Maximum Likelihood; Markov chain Monte Carlo; Metropolis Hastings algorithm; missing data; Simulation; Stochastic Differential Equation;

Other versions of this item:

Find related papers by JEL classification:


No references listed on IDEAS
You can help add them by filling out this form.


Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as in new window

Cited by:
This item has more than 25 citations. To prevent cluttering this page, these citations are listed on a separate page.


This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.


Access and download statistics


When requesting a correction, please mention this item's handle: RePEc:oxf:wpaper:1998-w10. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Caroline Wise).

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.