Please use this identifier to cite or link to this item: https://doi.org/10.1214/11-AIHP473
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dc.titleStein's method in high dimensions with applications
dc.contributor.authorRöllin, A.
dc.date.accessioned2014-10-28T05:15:32Z
dc.date.available2014-10-28T05:15:32Z
dc.date.issued2013-05
dc.identifier.citationRöllin, A. (2013-05). Stein's method in high dimensions with applications. Annales de l'institut Henri Poincare (B) Probability and Statistics 49 (2) : 529-549. ScholarBank@NUS Repository. https://doi.org/10.1214/11-AIHP473
dc.identifier.issn02460203
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/105396
dc.description.abstractLet h be a three times partially differentiable function on Rn, let X = (X1, +⋯, Xn) be a collection of real-valued random variables and let Z = (Z1, +⋯, Zn) be a multivariate Gaussian vector. In this article, we develop Stein's method to give error bounds on the difference Eh(X) - Eh(Z) in cases where the coordinates of X are not necessarily independent, focusing on the high dimensional case n→∞. In order to express the dependency structure we use Stein couplings, which allows for a broad range of applications, such as classic occupancy, local dependence, Curie-Weiss model, etc. We will also give applications to the Sherrington-Kirkpatrick model and last passage percolation on thin rectangles. © 2013 Association des Publications de l'Institut Henri Poincaré.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1214/11-AIHP473
dc.sourceScopus
dc.subjectCurie-Weiss model
dc.subjectGaussian interpolation
dc.subjectLast passage percolation on thin rectangles
dc.subjectSherrington-Kirkpatrick model
dc.subjectStein's method
dc.typeArticle
dc.contributor.departmentSTATISTICS & APPLIED PROBABILITY
dc.description.doi10.1214/11-AIHP473
dc.description.sourcetitleAnnales de l'institut Henri Poincare (B) Probability and Statistics
dc.description.volume49
dc.description.issue2
dc.description.page529-549
dc.description.codenAHPBA
dc.identifier.isiut000325834600009
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