Quasi-Monte Carlo for highly structured generalised response models

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dc.contributor.author Kuo, F. en_US
dc.contributor.author Dunsmuir, W. en_US
dc.contributor.author Sloan, I. en_US
dc.contributor.author Womersley, R. en_US
dc.contributor.author Wand, Matt en_US
dc.contributor.editor en_US
dc.date.accessioned 2012-02-02T04:17:31Z
dc.date.available 2012-02-02T04:17:31Z
dc.date.issued 2008 en_US
dc.identifier 2010000459 en_US
dc.identifier.citation Kuo F. et al. 2008, 'Quasi-Monte Carlo for highly structured generalised response models', Springer New York LLC, vol. 10, no. 2, pp. 239-275. en_US
dc.identifier.issn 1387-5841 en_US
dc.identifier.other C1UNSUBMIT en_US
dc.identifier.uri http://hdl.handle.net/10453/14509
dc.description.abstract Highly structured generalised response models, such as generalised linear mixed models and generalised linear models for time series regression, have become an indispensable vehicle for data analysis and inference in many areas of application. However, their use in practice is hindered by high-dimensional intractable integrals. Quasi-Monte Carlo (QMC) is a dynamic research area in the general problem of high-dimensional numerical integration, although its potential for statistical applications is yet to be fully explored. We survey recent research in QMC, particularly lattice rules, and report on its application to highly structured generalised response models. New challenges for QMC are identified and new methodologies are developed. QMC methods are seen to provide significant improvements compared with ordinary Monte Carlo methods. en_US
dc.language en_US
dc.publisher Springer New York LLC en_US
dc.relation.isbasedon http://dx.doi.org/10.1007/s11009-007-9045-3 en_US
dc.title Quasi-Monte Carlo for highly structured generalised response models en_US
dc.parent Methodology and Computing in Applied Probability en_US
dc.journal.volume 10 en_US
dc.journal.number 2 en_US
dc.publocation United States en_US
dc.identifier.startpage 239 en_US
dc.identifier.endpage 275 en_US
dc.cauo.name SCI.Mathematical Sciences en_US
dc.conference Verified OK en_US
dc.for 010400 en_US
dc.personcode 0000065161 en_US
dc.personcode 0000065162 en_US
dc.personcode 0000065163 en_US
dc.personcode 110509 en_US
dc.personcode 0000065164 en_US
dc.percentage 100 en_US
dc.classification.name Statistics en_US
dc.classification.type FOR-08 en_US
dc.edition en_US
dc.custom en_US
dc.date.activity en_US
dc.location.activity en_US
dc.description.keywords Generalised linear mixed models - High-dimensional integration - Lattice rules - Longitudinal data analysis - Maximum likelihood - Quasi-Monte Carlo - Semiparametric regression - Serial dependence - Time series regression en_US
dc.staffid en_US

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