On variance stabilisation in Population Monte Carlo by double Rao-Blackwellisation
AbstractPopulation Monte Carlo has been introduced as a sequential importance sampling technique to overcome poor fit of the importance function. The performance of the original Population Monte Carlo algorithm is compared with a modified version that eliminates the influence of the transition particle via a double Rao-Blackwellisation. This modification is shown to improve the exploration of the modes through a large simulation experiment on posterior distributions of mean mixtures of distributions.
Download InfoIf 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.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Bibliographic InfoArticle provided by Elsevier in its journal Computational Statistics & Data Analysis.
Volume (Year): 54 (2010)
Issue (Month): 3 (March)
Contact details of provider:
Web page: http://www.elsevier.com/locate/csda
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Cappé, Olivier & Guillin, Arnaud & Marin, Jean-Michel & Robert, Christian P., 2004. "Population Monte Carlo," Economics Papers from University Paris Dauphine 123456789/6072, Paris Dauphine University.
- repec:ner:dauphi:urn:hdl:123456789/6069 is not listed on IDEAS
- Celeux, Gilles & Marin, Jean-Michel & Robert, Christian P., 2006. "Iterated importance sampling in missing data problems," Economics Papers from University Paris Dauphine 123456789/6215, Paris Dauphine University.
- Marin, Jean-Michel & Mengersen, Kerrie & Robert, Christian P., 2005. "Bayesian Modelling and Inference on Mixtures of Distributions," Economics Papers from University Paris Dauphine 123456789/6069, Paris Dauphine University.
- Marin, Jean-Michel & Robert, Christian P., 2007. "Bayesian Core: A practical approach to computational Bayesian statistics," Economics Papers from University Paris Dauphine 123456789/1906, Paris Dauphine University.
- repec:ner:dauphi:urn:hdl:123456789/6072 is not listed on IDEAS
- Celeux, Gilles & Marin, Jean-Michel & Robert, Christian P., 2006. "Iterated importance sampling in missing data problems," Computational Statistics & Data Analysis, Elsevier, vol. 50(12), pages 3386-3404, August.
- repec:ner:dauphi:urn:hdl:123456789/6215 is not listed on IDEAS
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Wendy Shamier).
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.