Please use this identifier to cite or link to this item:https://hdl.handle.net/20.500.12259/83050
Type of publication: Straipsnis kitose duomenų bazėse / Article in other databases (S4)
Field of Science: Matematika / Mathematics (N001)
Author(s): Petrauskas, Edmundas;Rupšys, Petras
Title: Age-varying bivariate distribution models for growth prediction
Is part of: Mathematical models for engineering science: International conference on mathematical models for engineering science (MMES'10) , Puerto De La Cruz, Tenerife, November 30 - December 2, 2010. Puerto De La Cruz: Published by WSEAS Press, 2010
Extent: p. 250-255
Date: 2010
Keywords: Age-varying bivariate density;Diameter;Height;Normal bivariate copula;Stochastic differential equation
ISBN: 978-960-474-252-3
Abstract: Abstract— Height-diamelcr models are classically analyzed by fixed or mixed linear and non-linear regression models. In order to possess the among-plot variability, we propose stochastic differential equations thai are deduced from the standard deterministic dynamic ordinary differential equations by adding the process variability to the growth dynamic. The advantage of the stochastic differential equation framework is that it analyzes a residual variability, corresponding to measurements error, and an individual variability to represent heterogeneity between subjects. An analysis of 1575 Scots pine (Pimis sylvestris) trees provided the data for this study. The results are implemented in the symbolic computational language MAPLE
Internet: https://hdl.handle.net/20.500.12259/83050
Affiliation(s): Vytauto Didžiojo universitetas
Žemės ūkio akademija
Appears in Collections:Universiteto mokslo publikacijos / University Research Publications

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