Grid based variational approximations
Variational methods for approximate Bayesian inference provide fast, flexible, deterministic alternatives to Monte Carlo methods. Unfortunately, unlike Monte Carlo methods, variational approximations cannot, in general, be made to be arbitrarily accurate. This paper develops grid-based variational approximations which endeavor to approximate marginal posterior densities in a spirit similar to the Integrated Nested Laplace Approximation (INLA) of Rue etÂ al. (2009)but which may be applied in situations where INLA cannot be used. The method can greatly increase the accuracy of a base variational approximation, although not in general to arbitrary accuracy. The methodology developed is at least reasonably accurate on all of the examples considered in the paper.
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.
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.
References listed on IDEAS
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.:
- Peter Hall & K. Humphreys & D. M. Titterington, 2002. "On the adequacy of variational lower bound functions for likelihood-based inference in Markovian models with missing values," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(3), pages 549-564.
- Consonni, Guido & Marin, Jean-Michel, 2007. "Mean-field variational approximate Bayesian inference for latent variable models," Computational Statistics & Data Analysis, Elsevier, vol. 52(2), pages 790-798, October.
- Håvard Rue & Sara Martino & Nicolas Chopin, 2009. "Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 71(2), pages 319-392.
- Ormerod, J. T. & Wand, M. P., 2010. "Explaining Variational Approximations," The American Statistician, American Statistical Association, vol. 64(2), pages 140-153.
When requesting a correction, please mention this item's handle: RePEc:eee:csdana:v:55:y:2011:i:1:p:45-56. 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: (Dana Niculescu)
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.