Please use this identifier to cite or link to this item:https://hdl.handle.net/20.500.12259/82458
Type of publication: Straipsnis Clarivate Analytics Web of Science ar/ir Scopus / Article in Clarivate Analytics Web of Science or / and Scopus (S1)
Field of Science: Matematika / Mathematics (N001);Miškotyra / Forestry (A004)
Author(s): Rupšys, Petras;Petrauskas, Edmundas
Title: Quantifying tree diameter distributions with one-dimensional diffusion processes
Is part of: Journal of Biological Systems. Singapore : World Scientific Publishing Co, Vol. 18, iss. 1 (2010)
Extent: p. 205-221
Date: 2010
Keywords: Diameter;CIR Model;Logistic Model;Shapiro-Wilk Statistic;Transition Density;Vasicek Model
Abstract: This study presents diffusion processes methodology on tree diameter distribution problem. We use stochastic differential equation methodology to derive a univariate age-dependent probability density function of a tree diameter distribution. The purpose of this paper is to investigate the relationship between the stochastic linear and logistic shape diameter growth models and diameter distribution laws. We establish the probabilistic characteristics of stochastic growth models, such as the univariate transition probability density of tree diameter, the mean and variance of tree diameter. We carry out comparison of proposed continuous time stochastic models on the basis of Hong-Li, Gini, Shapiro-Wilk goodness-of-fit statistics and normal probability plot. Parameter estimations are based on discrete observations over age of trees. To model the tree diameter distribution, as an illustrative experience, a real data set from repeated measurements on a permanent sample plot of pine (Pinus sylvestris) stand in the Kazlu Ruda district at Lithuania is used. The results are implemented in the symbolic computational language MAPLE
Internet: https://hdl.handle.net/20.500.12259/82458
Affiliation(s): Vytauto Didžiojo universitetas
Žemės ūkio akademija
Appears in Collections:Universiteto mokslo publikacijos / University Research Publications

Files in This Item:
marc.xml7.1 kBXMLView/Open

MARC21 XML metadata

Show full item record
Export via OAI-PMH Interface in XML Formats
Export to Other Non-XML Formats


CORE Recommender

WEB OF SCIENCETM
Citations 1

10
checked on Sep 12, 2020

Page view(s)

56
checked on Feb 4, 2020

Download(s)

10
checked on Feb 4, 2020

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.