Royal Statistical Society
Statistical Computing Section Meeting
Wednesday 27 March, 1:30pm - 5:30pm (tea at 3pm)
at
The Royal Statistical Society, 12 Errol St, London EC1
(nearest UG stations, Barbican, Moorgate & Old Street)
The potential of High Performance Computing (HPC) for
statistical modelling in the social, economic and
medical sciences
This half day meeting reviews some of the current and
potential roles of HPC and the GRID (a virtual
supercomputer) for the analysis of observational data.
All are welcome. There is no need to book.
13:30 - 14:15 R. Crouchley and R. Fligelstone
(University of Lancaster)
"The relevance of HPC for the analysis of
observational data"
Synopsis: Observational social science data sets are
relatively small, but the intricacies of human behaviour
create a complex set of interdependencies between the
variables of a data set. We illustrate how the complex and
comprehensive nature of the models that reflect these
intricacies take our analysis beyond what can be usefully
estimated on a PC.
2:15pm - 3pm R. Ecochard (Lyon) and D.G. Clayton (Cambridge)
"Fitting complex random effect models with standard
software using data augmentation"
Synopsis: Clayton and Rasbash (1999) have proposed an
alternating imputation-posterior (AIP) algorithm that
provides an easy way of dealing with large and complicated
crossed-hierarchy designs. The AIP algorithm may be
implemented in two distinct ways: first by running the
steps sequentially and secondly as parallel tasks with
multi-processor architecture or on separate computers in
network. We illustrate the approaches on an example of
artificial insemination by donor.
3pm - 3:30pm Tea
3:30pm - 4:15pm J. A. Doornik (Nuffield College, Oxford)
"HPC in Econometrics using Distributed Ox"
Synopsis: In a recent paper presented to the Royal Society,
Doornick, Hendry and Shephard argued the need for HPC in
econometrics and statistics. We identified a shortage of
easy-to-use statistical software for HPC, and provided a
solution based on the Ox matrix programming language. We
now extend this work and illustrate Ox for the simulation
of distributions for outlier detection procedures in
generalized autoregressive conditional heteroscedasticity
(GARCH) models, and simulation-based estimation of
stochastic volatility models.
4:15pm - 5pm J. Rasbash (Institute of Education, London) and
M. Bull (Edinburgh Parallel Computing Centre)
"Parallel implementation of a multilevel modelling
software package"
Synopsis: This talk describes a portable parallel
implementation of the IGLS algorithm used by the software
package MLwiN for fitting random effects models. Particular
attention is paid to crossed and multiple membership random
effects models, which pose significant computational
challenges for the IGLS algorithm which is optimised for
nested random effects. Comparisons of performance between
the sequential and parallel approaches across a range of
shared memory parallel architectures are given.
5:00pm - 5:30pm Discussion and close
All are welcome. There is no need to book.
http://www.gla.ac.uk/External/RSS/RSScomp/
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Suzanne Evans
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