GPU accelerated MCMC for modelling terrorist activity
White, Gentry & Porter, Michael D. (2013) GPU accelerated MCMC for modelling terrorist activity. Computational Statistics and Data Analysis, 71, pp. 643-651.
The use of graphical processing unit (GPU) parallel processing is becoming a part of mainstream statistical practice. The reliance of Bayesian statistics on Markov Chain Monte Carlo (MCMC) methods makes the applicability of parallel processing not immediately obvious. It is illustrated that there are substantial gains in improved computational time for MCMC and other methods of evaluation by computing the likelihood using GPU parallel processing. Examples use data from the Global Terrorism Database to model terrorist activity in Colombia from 2000 through 2010 and a likelihood based on the explicit convolution of two negative-binomial processes. Results show decreases in computational time by a factor of over 200. Factors influencing these improvements and guidelines for programming parallel implementations of the likelihood are discussed.
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|Item Type:||Journal Article|
|Keywords:||GPU, MCMC, Terrorism, Self-exciting Model|
|Subjects:||Australian and New Zealand Standard Research Classification > MATHEMATICAL SCIENCES (010000) > STATISTICS (010400) > Applied Statistics (010401)|
|Divisions:||Current > Schools > School of Mathematical Sciences
Current > QUT Faculties and Divisions > Science & Engineering Faculty
|Copyright Owner:||Copyright 2014 Elsevier|
|Copyright Statement:||This is the author’s version of a work that was accepted for publication in Computational Statistics and Data Analysis. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Computational Statistics and Data Analysis, [VOL 71, (2014)] DOI: 10.1016/j.csda.2013.03.027|
|Deposited On:||20 Mar 2014 00:02|
|Last Modified:||21 Mar 2014 00:58|
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