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Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/33859
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dc.contributor.authorNavarro, D.-
dc.date.issued2004-
dc.identifier.citationNeural Computation, 2004; 16(9):1763-1768-
dc.identifier.issn0899-7667-
dc.identifier.issn1530-888X-
dc.identifier.urihttp://hdl.handle.net/2440/33859-
dc.description.-
dc.description.abstractAn applied problem is discussed in which two nested psychological models of retention are compared using minimum description length (MDL). The standard Fisher information approximation to the normalized maximum likelihood is calculated for these two models, with the result that the full model is assigned a smaller complexity, even for moderately large samples. A geometric interpretation for this behavior is considered, along with its practical implications-
dc.description.statementofresponsibilityDaniel J. Navarro-
dc.language.isoen-
dc.publisherM I T Press-
dc.relation.isreplacedby2440/90738-
dc.relation.isreplacedbyhttp://hdl.handle.net/2440/90738-
dc.rightsCopyright © 2004 Massachusetts Institute of Technology-
dc.source.urihttp://dx.doi.org/10.1162/0899766041336378-
dc.subjectHumans-
dc.subjectData Interpretation, Statistical-
dc.subjectLikelihood Functions-
dc.subjectMental Processes-
dc.subjectModels, Psychological-
dc.subjectRetention, Psychology-
dc.titleA note on the applied use of MDL approximations-
dc.typeJournal article-
dc.identifier.doi10.1162/0899766041336378-
pubs.publication-statusPublished-
dc.identifier.orcidNavarro, D. [0000-0001-7648-6578]-
Appears in Collections:Aurora harvest 7
Psychology publications

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