Accuracy of binned kernel functional approximations

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Show simple item record Gonzalez-Manteiga, W Sanchez-Sellero, C Wand, M 2014-04-03T01:04:32Z 1996-01
dc.identifier.citation Computational Statistics and Data Analysis, 1996, 22 (1), pp. 1 - 16
dc.identifier.issn 0167-9473
dc.identifier.other C1UNSUBMIT en_US
dc.description.abstract Virtually all common bandwidth selection algorithms are based on a certain type of kernel functional estimator. Such estimators can be computationally very expensive, so in practice they are often replaced by fast binned approximations. This is especially worthwhile when the bandwidth selection method involves iteration. Results for the accuracy of these approximations are derived and then used to provide an understanding of the number of binning grid points required to achieve a given level of accuracy. Our results apply to both univariate and multivariate settings. Multivariate contexts are of particular interest since the cost due to having a higher number of grid points can be quite significant.
dc.format Jessica Robinson
dc.publisher Elsevier
dc.relation.isbasedon 10.1016/0167-9473(96)88030-3
dc.title Accuracy of binned kernel functional approximations
dc.type Journal Article
dc.parent Computational Statistics and Data Analysis
dc.journal.volume 1
dc.journal.volume 22
dc.journal.number 1 en_US
dc.publocation Netherlands en_US
dc.publocation Hong Kong
dc.identifier.startpage 1 en_US
dc.identifier.endpage 16 en_US SCI.Mathematical Sciences en_US
dc.conference Verified OK en_US
dc.conference Association for Computer-Aided Architectural Design Research in Asia annual conference
dc.for 0104 Statistics
dc.personcode 110509
dc.percentage 100 en_US Statistics en_US
dc.classification.type FOR-08 en_US
dc.edition en_US
dc.custom en_US en_US 2010-04-07
dc.location.activity en_US
dc.location.activity The Chinese University of Hong Kong
dc.description.keywords bandwidth selection
dc.description.keywords binned kernel estimator
dc.description.keywords density estimation
dc.description.keywords kernel estimator
dc.description.keywords SQUARED DENSITY DERIVATIVES
dc.description.keywords CROSS-VALIDATION
dc.description.keywords HISTOGRAMS
dc.description.keywords ESTIMATORS
dc.description.keywords CHOICE
pubs.embargo.period Not known
pubs.organisational-group /University of Technology Sydney
pubs.organisational-group /University of Technology Sydney/Faculty of Science
utslib.copyright.status Closed Access 2015-04-15 12:17:09.805752+10
pubs.consider-herdc false
utslib.collection.history Closed (ID: 3)
utslib.collection.history School of Mathematical Sciences (ID: 340)

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