Please use this identifier to cite or link to this item:https://hdl.handle.net/20.500.12259/86316
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dc.contributor.authorRupšys, Petras-
dc.coverage.spatialDE-
dc.date.accessioned2019-05-17T20:09:42Z-
dc.date.available2019-05-17T20:09:42Z-
dc.date.issued2013-
dc.identifier.isbn9789400761896-
dc.identifier.otherVDU02-000047924-
dc.identifier.urihttps://hdl.handle.net/20.500.12259/86316-
dc.description.abstractStem taper process measured repeatedly among a series of individual trees is standardly analyzed by fixed and mixed regression models. This stem taper process can be adequately modeled by parametric stochastic differential equations (SDEs). We focus on the segmented stem taper model defined by the Gompertz, geometric Brownian motion and Ornstein-Uhlenbeck stochastic processes. This class of models enables the representation of randomness in the taper dynamics. The parameter estimators are evaluated by maximum likelihood procedure. The SDEs stem taper models were fitted to a data set of Scots pine trees collected across the entire Lithuanian territory. Comparison of the predicted stem taper and stem volume with those obtained using regression based models showed a predictive power to the SDEs modelsen
dc.description.sponsorshipVytauto Didžiojo universitetas-
dc.description.sponsorshipŽemės ūkio akademija-
dc.format.extentp. 121-133-
dc.language.isoen-
dc.relation.ispartofIAENG Transactions on Engineering Technologies : Special Volume of the World Congress on Engineering 2012. Dordrecht; New York : Springer, 2013-
dc.relation.ispartofseries(Lecture Notes in Electrical Engineering 229)-
dc.relation.isreferencedbySpringerLINK-
dc.subjectDiameteren
dc.subjectGeometric Brownian motionen
dc.subjectGompertz processen
dc.subjectOrnstein-Uhlenbeck processen
dc.subjectTaperen
dc.subjectTransition probability densityen
dc.subjectStochastic differential equationen
dc.subject.classificationKnygos dalis / Part of book (Y)-
dc.subject.otherMatematika / Mathematics (N001)-
dc.titleThe Further Development of Stem Taper and Volume Models Defined by Stochastic Differential Equationsen
dc.typebook part-
dcterms.bibliographicCitation26-
dc.date.updated2019-10-01T16:05Z-
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local.typeY-
item.fulltextNo Fulltext-
item.grantfulltextnone-
crisitem.author.deptMiškų ir ekologijos fakultetas-
Appears in Collections:Universiteto mokslo publikacijos / University Research Publications
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