Title	Towards not being afraid of the big bad data set
Creator	Roberts, Gareth 0.
Publisher	Banff International Research Station for Mathematical Innovation and Discovery
Date Issued	2015-06-02T15:33
Description	This talk will present the foundations behind a new algorithm for systematic error-free Monte Carlo simulation from intractable target distributions. The main motivation behind the work is to construct a method for exploring posterior distributions for Bayesian analyses of extremely large datasets where computation of the likelihood function at each iteration of an algorithm is prohibitively expensive. The algorithm is a continuous time sequential Monte Carlo procedure which extends many of the ideas used in exact simulation from diffusion sample paths.
Extent	56 minutes
Subject	Mathematics; Probability theory and stochastic processes; Statistics; Operation research
Type	Moving Image
File Format	video/mp4
Language	eng
Notes	Author affiliation: University of Warwick
Series	BIRS Workshop Lecture Videos (Banff, Alta)
Date Available	2016-01-04
Provider	Vancouver : University of British Columbia Library
Rights	Attribution-NonCommercial-NoDerivs 2.5 Canada
DOI	10.14288/1.0221664
URI	http://hdl.handle.net/2429/56148
Affiliation	Non UBC
Peer Review Status	Unreviewed
Scholarly Level	Faculty
Rights URI	http://creativecommons.org/licenses/by-nc-nd/2.5/ca/
Aggregated Source Repository	DSpace

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