Study on Dominant Height Growth of Fir Plantations Based on a Nonlinear Mixed Modeling Approach for Longitudinal Data / 基于纵向数据非线性混合模型的杉木林优势木平均高研究

The improvement on the dominant height growth implies in better productivity estimation due to the forest height growth is directly related with the site characteristics and forest productivity. A modified Richards growth model with nonlinear mixed effects is simulated used SAS software for modeling...

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Bibliographic Details
Published inForest research (Beijing) Vol. 24; no. 1; p. 68
Main Author 李春明
Format Journal Article
LanguageChinese
Published Beijing Chinese Academy of Forestry 01.01.2011
Subjects
Plantations
Regression analysis
Time series
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Summary:The improvement on the dominant height growth implies in better productivity estimation due to the forest height growth is directly related with the site characteristics and forest productivity. A modified Richards growth model with nonlinear mixed effects is simulated used SAS software for modeling fir plantation dominant height growth in conjunction with different plantation density in Dagangshan Experiment Bureau of Jiangxi Province. Akaike Information Criterion(AIC) and Bayesian Information Criterion(BIC) were used in model performance evaluation. Within-plot time series error autocorrelation of dominant height growth data and different plantation density expressed with dummy variable were taken into account in mixed model. Finally, the precision of mixed models was compared with the precision of conventional nonlinear ordinary regression analysis method based on validation data. The result showed that the precision of modified Richards forms nonlinear mixed effect model which takes into account plot’s ra
ISSN:1001-1498