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dc.contributor.authorAmmon, Christian
dc.contributor.authorSpilke, Joachim
dc.contributor.editorSchiefer, Gerhard
dc.contributor.editorWagner, Peter
dc.contributor.editorMorgenstern, Marlies
dc.contributor.editorRickert, Ursula
dc.date.accessioned2019-10-15T12:24:20Z
dc.date.available2019-10-15T12:24:20Z
dc.date.issued2004
dc.identifier.isbn3-88579-378-4
dc.identifier.issn1617-5468
dc.identifier.urihttp://dl.gi.de/handle/20.500.12116/29030
dc.description.abstractMixed linear models can be used to improve the informational value of milk yield forecasts. For this purpose two different functional approaches for modelling lactation curves are as well compared as three linear mixed models with varying random effects of individual animals and lactation numbers. It can be shown that more complex random regression models fit significantly better than fixed regression models.de
dc.language.isode
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofIntegration und Datensicherheit – Anforderungen, Konflikte und Perspektiven, Referate der 25. GIL Jahrestagung
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-49
dc.titleVergleich von Fixed- und Random-Regression Modellen bei verschiedenen Funktionsansätzen für Laktationskurven zur Vorhersage von Milchleistungende
dc.typeText/Conference Paper
dc.pubPlaceBonn
mci.reference.pages149-152
mci.conference.sessiontitleRegular Research Papers
mci.conference.locationBonn
mci.conference.date8.-10. September 2004


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