Realtime sequential inference of static parameters with expensive likelihood calculations
AbstractA methodology is developed for making inference about parameters of a possible covert chemical or biological atmospheric release from sensor readings. The key difficulty in performing this inference is that the results must be obtained in a very short timescale (5 min) to make use of the inference for protection. The methodology that is developed uses some of the components in a sequential Monte Carlo algorithm. However, this inference problem is different from many other sequential Monte Carlo problems, in that there are no state evolution equations, the forward model is highly non-linear and the likelihoods are non-Gaussian. The algorithm that is developed can use stored output from complex physics models for more rapid update of the posterior from new data without having to rerun the models. The use of differential evolution Markov chain sampling allows new samples to diverge rapidly from degenerate sample sets. Results for inferences made of atmospheric releases (both real and simulated) of material are presented, demonstrating that the sampling scheme performs adequately despite constraints of a short time span for calculations. Copyright (c) British Crown copyright 2009 Dstl-published with the permission of the Controller of Her Majesty's Stationery Office.
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 Royal Statistical Society in its journal Journal of the Royal Statistical Society: Series C (Applied Statistics).
Volume (Year): 58 (2009)
Issue (Month): 5 ()
Contact details of provider:
Postal: 12 Errol Street, London EC1Y 8LX, United Kingdom
Web page: http://wileyonlinelibrary.com/journal/rssc
More information through EDIRC
You can help add them by filling out this form.
reading list or among the top items on IDEAS.Access and download statisticsgeneral 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: (Wiley-Blackwell Digital Licensing) or (Christopher F. Baum).
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.