A cheaper way to compute generalized cross-validation as a stopping rule for linear stationary iterative methods

dc.creatorSantos, RJ
dc.creatorDe Pierro, AR
dc.date2003
dc.dateJUN
dc.date2014-11-16T20:38:54Z
dc.date2015-11-26T17:26:43Z
dc.date2014-11-16T20:38:54Z
dc.date2015-11-26T17:26:43Z
dc.date.accessioned2018-03-29T00:13:52Z
dc.date.available2018-03-29T00:13:52Z
dc.identifierJournal Of Computational And Graphical Statistics. Amer Statistical Assoc, v. 12, n. 2, n. 417, n. 433, 2003.
dc.identifier1061-8600
dc.identifierWOS:000183370300009
dc.identifier10.1198/1061860031815
dc.identifierhttp://www.repositorio.unicamp.br/jspui/handle/REPOSIP/52858
dc.identifierhttp://www.repositorio.unicamp.br/handle/REPOSIP/52858
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/52858
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1284613
dc.descriptionWe apply generalized cross-validation (GCV) as a stopping rule for general linear stationary iterative methods for solving very large-scale, ill-conditioned problems. We present a new general formula for the influence operator for these methods and, using this formula and a Monte Carlo approach, we show how to compute the GCV function at a cheaper cost. Then we apply our approach to a well known iterative method (ART) with simulated data in positron emission tomography (PET).
dc.description12
dc.description2
dc.description417
dc.description433
dc.languageen
dc.publisherAmer Statistical Assoc
dc.publisherAlexandria
dc.publisherEUA
dc.relationJournal Of Computational And Graphical Statistics
dc.relationJ. Comput. Graph. Stat.
dc.rightsfechado
dc.sourceWeb of Science
dc.subjectemission tomography
dc.subjectill-posed problems
dc.subjectparameter estimation
dc.subjectPositron Emission Tomography
dc.subjectLeast-squares Problems
dc.subjectTruncated Iteration
dc.subjectEm Algorithm
dc.subjectRegularization
dc.subjectEquivalence
dc.subjectRestoration
dc.titleA cheaper way to compute generalized cross-validation as a stopping rule for linear stationary iterative methods
dc.typeArtículos de revistas


Este ítem pertenece a la siguiente institución