Use of nonparametric regression methods for developing a local stem form model

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41320%2F14%3A64999" target="_blank" >RIV/60460709:41320/14:64999 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Use of nonparametric regression methods for developing a local stem form model
Original language description
A local mean stem curve of spruce was represented using regression splines. Abilities of smoothing spline and P-spline to model the mean stem curve were evaluated using data of 85 carefully measured stems of Norway spruce. For both techniques the optimalamount of smoothing was investigated in dependence on the number of training stems using a cross-validation method. Representatives of main groups of parametric models ? single models, segmented models and models with variable coefficient ? were compared with spline models using five statistic criteria. Both regression splines performed comparably or better as all representatives of parametric models independently of the numbers of stems used as training data.
Czech name
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Czech description
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Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
GK - Forestry
OECD FORD branch
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Project
<a href="/en/project/QI102A079" target="_blank" >QI102A079: Research on biomass of broadleaved species</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2014
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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