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dc.contributor.authorSánchez Pla, Àlex
dc.date.accessioned2007-12-04T19:30:31Z
dc.date.available2007-12-04T19:30:31Z
dc.date.issued1990
dc.identifier.citationSànchez, Àlex (Sànchez Pla). "Efficient bootstrap simulation; an overview". Qüestiió. 1990, vol. 14, núm. 1-3
dc.identifier.issn0210-8054 (versió paper)
dc.identifier.urihttp://hdl.handle.net/2099/3988
dc.description.abstractTwo basic sources of error are associated to the use of bootstrap methods: one is derived from the fact that the true distribution is substituted by a suitable estimate, and the other is simulation errors. Some techniques to reduce or quantify these errors are discussed in this work. Some of them such as importance sampling or antithetic variates are adapted from classical Monte Carlo swindles, whereas others such as the centered and the balanced bootstrap, are more specific. The existence of common methodological trends, such as the use of influence functions and Von Mises expansions to estimate the variance of the methods is emphasized.
dc.format.extent46 p.
dc.language.isoeng
dc.publisherUniversitat Politècnica de Barcelona. Centre de Càlcul
dc.rightsAttribution-NonCommercial-NoDerivs 2.5 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/2.5/es/
dc.subject.lcshInference
dc.subject.otherEfficient bootstrap simulation
dc.subject.otherCentered bootstrap
dc.subject.otherLinear bootstrap
dc.subject.otherBalanced bootstrap
dc.subject.otherImportance Sampling
dc.subject.otherAntithetic sampling
dc.subject.otherDelta method
dc.subject.otherInfluence functions
dc.titleEfficient bootstrap simulation; an overview
dc.typeArticle
dc.subject.lemacInferència
dc.subject.amsClassificació AMS::62 Statistics::62G Nonparametric inference
dc.rights.accessOpen Access
local.ordre4
local.personalitzacitaciotrue


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