FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2095687430> ?p ?o ?g. }

• W2095687430 endingPage "2759" @default.
• W2095687430 startingPage "2733" @default.
• W2095687430 abstract "Bayesian inference from high-dimensional data involves the integration over a large number of model parameters. Accurate evaluation of such high-dimensional integrals raises a unique set of issues. These issues are illustrated using the exemplar of model selection for principal component analysis (PCA). A Bayesian model selection criterion, based on a Laplace approximation to the model evidence for determining the number of signal principal components present in a data set, has previously been show to perform well on various test data sets. Using simulated data we show that for d-dimensional data and small sample sizes, N, the accuracy of this model selection method is strongly affected by increasing values of d. By taking proper account of the contribution to the evidence from the large number of model parameters we show that model selection accuracy is substantially improved. The accuracy of the improved model evidence is studied in the asymptotic limit d ! ∞ at fixed ratio α = N=d, with α < 1. In this limit, model selection based upon the improved model evidence agrees with a frequentist hypothesis testing approach." @default.
• W2095687430 created "2016-06-24" @default.
• W2095687430 creator A5014404477 @default.
• W2095687430 date "2008-12-01" @default.
• W2095687430 modified "2023-09-23" @default.
• W2095687430 title "Automatic PCA Dimension Selection for High Dimensional Data and Small Sample Sizes" @default.
• W2095687430 cites W1494904807 @default.
• W2095687430 cites W1520752838 @default.
• W2095687430 cites W1534201377 @default.
• W2095687430 cites W183241451 @default.
• W2095687430 cites W1861517257 @default.
• W2095687430 cites W1934021597 @default.
• W2095687430 cites W1971565000 @default.
• W2095687430 cites W1986817398 @default.
• W2095687430 cites W2005522417 @default.
• W2095687430 cites W2006785121 @default.
• W2095687430 cites W2009188663 @default.
• W2095687430 cites W2026988331 @default.
• W2095687430 cites W2034857737 @default.
• W2095687430 cites W2036248065 @default.
• W2095687430 cites W2051852314 @default.
• W2095687430 cites W2060581589 @default.
• W2095687430 cites W2066459155 @default.
• W2095687430 cites W2075032250 @default.
• W2095687430 cites W2091571775 @default.
• W2095687430 cites W2103633133 @default.
• W2095687430 cites W2106084579 @default.
• W2095687430 cites W2109363337 @default.
• W2095687430 cites W2125027820 @default.
• W2095687430 cites W2133028937 @default.
• W2095687430 cites W2140095548 @default.
• W2095687430 cites W2146610201 @default.
• W2095687430 cites W2148694408 @default.
• W2095687430 cites W2157752701 @default.
• W2095687430 cites W2165918462 @default.
• W2095687430 cites W2170706425 @default.
• W2095687430 cites W2294460823 @default.
• W2095687430 cites W2911546748 @default.
• W2095687430 cites W3022776974 @default.
• W2095687430 cites W3141350557 @default.
• W2095687430 hasPublicationYear "2008" @default.
• W2095687430 type Work @default.
• W2095687430 sameAs 2095687430 @default.
• W2095687430 citedByCount "18" @default.
• W2095687430 countsByYear W20956874302012 @default.
• W2095687430 countsByYear W20956874302013 @default.
• W2095687430 countsByYear W20956874302014 @default.
• W2095687430 countsByYear W20956874302015 @default.
• W2095687430 countsByYear W20956874302016 @default.
• W2095687430 countsByYear W20956874302017 @default.
• W2095687430 countsByYear W20956874302018 @default.
• W2095687430 countsByYear W20956874302019 @default.
• W2095687430 crossrefType "journal-article" @default.
• W2095687430 hasAuthorship W2095687430A5014404477 @default.
• W2095687430 hasConcept C105795698 @default.
• W2095687430 hasConcept C107673813 @default.
• W2095687430 hasConcept C129848803 @default.
• W2095687430 hasConcept C134306372 @default.
• W2095687430 hasConcept C142291917 @default.
• W2095687430 hasConcept C151201525 @default.
• W2095687430 hasConcept C154945302 @default.
• W2095687430 hasConcept C160234255 @default.
• W2095687430 hasConcept C162376815 @default.
• W2095687430 hasConcept C168136583 @default.
• W2095687430 hasConcept C202444582 @default.
• W2095687430 hasConcept C22243797 @default.
• W2095687430 hasConcept C27438332 @default.
• W2095687430 hasConcept C33676613 @default.
• W2095687430 hasConcept C33923547 @default.
• W2095687430 hasConcept C41008148 @default.
• W2095687430 hasConcept C58489278 @default.
• W2095687430 hasConcept C70518039 @default.
• W2095687430 hasConcept C81917197 @default.
• W2095687430 hasConcept C93959086 @default.
• W2095687430 hasConceptScore W2095687430C105795698 @default.
• W2095687430 hasConceptScore W2095687430C107673813 @default.
• W2095687430 hasConceptScore W2095687430C129848803 @default.
• W2095687430 hasConceptScore W2095687430C134306372 @default.
• W2095687430 hasConceptScore W2095687430C142291917 @default.
• W2095687430 hasConceptScore W2095687430C151201525 @default.
• W2095687430 hasConceptScore W2095687430C154945302 @default.
• W2095687430 hasConceptScore W2095687430C160234255 @default.
• W2095687430 hasConceptScore W2095687430C162376815 @default.
• W2095687430 hasConceptScore W2095687430C168136583 @default.
• W2095687430 hasConceptScore W2095687430C202444582 @default.
• W2095687430 hasConceptScore W2095687430C22243797 @default.
• W2095687430 hasConceptScore W2095687430C27438332 @default.
• W2095687430 hasConceptScore W2095687430C33676613 @default.
• W2095687430 hasConceptScore W2095687430C33923547 @default.
• W2095687430 hasConceptScore W2095687430C41008148 @default.
• W2095687430 hasConceptScore W2095687430C58489278 @default.
• W2095687430 hasConceptScore W2095687430C70518039 @default.
• W2095687430 hasConceptScore W2095687430C81917197 @default.
• W2095687430 hasConceptScore W2095687430C93959086 @default.
• W2095687430 hasIssue "92" @default.
• W2095687430 hasLocation W20956874301 @default.
• W2095687430 hasOpenAccess W2095687430 @default.
• W2095687430 hasPrimaryLocation W20956874301 @default.

• next