摘要
以黑龙江省七台河市林业局金沙林场9株人工落叶松6825对早、晚材管胞长度样品数据为例,选择6个常用方程进行非线性回归分析,把拟合精度最高的Richards模型作为早、晚材管胞长度基础模型y=β1[1-exp(-β2x)]β3+ε。基于Richards模型,利用非线性混合模型技术构建落叶松早、晚材管胞长度混合效应模型yij=(β1+b1i){1-exp[-(β2+b2i)t]}β3+b3i+εij。结果表明:当对早材管胞长度进行拟合时,b1i、b2i、b3i同时作为随机参数时早材管胞长度模型拟合最好;当对晚材管胞长度进行拟合时,b1i、b2i、b3i同时作为随机参数时晚材管胞长度模型拟合最好;一阶自回归模型AR(1)能够较好地表达树木内误差相关性;同时考虑随机效应和时间序列相关性结构能够提高落叶松早、晚材管胞长度混合模型的预测精度。
The sample data was based on 6 825 pairs of earlywood and latewood tracheid length samples of 9 trees from dahurian larch （Larix gmelinii Rupr. ） plantations located in Qitaihe Forest Bureau in Heilongjiang Province, northeastern China. Six functions were selected using nonlinear regression analysis. The Richards model y =/31 [ 1 - exp （ -/32x） ]83 ＋ ~ was selected to model earlywood and latewood tracheid length based on goodness-of-fit statistics. Nonlinear mixed-effects modeling approach was used to build mixed-effects models of earlywood and latewood tracheid length based on Richards model Yij = （β1＋ b,） t l -exp[ - （β2 ＋ b2i）t] }β3＋b3, ＋ εij The results showed that Richards model with parameters b1i, b2i, b3i as random effects showed the best performance for both earlywood and latewood tracheid length. Time series correlation structures AR （1） describe error correlation within tree well. Prediction precision of earlywood and latewood tracheid length mixed models could be improved through considering both random effects and time series correlation structures.
出处
《北京林业大学学报》
CAS
CSCD
北大核心
2013年第3期18-23,共6页
Journal of Beijing Forestry University
基金
中央高校基本科研业务费专项(DL12DA01
DL12EB07-2)
国家自然科学基金项目(31170591)
黑龙江省自然科学基金项目(C201111)
关键词
管胞长度
非线性混合模型
随机效应
相关性结构
落叶松
tracheid length
nonlinear mixed model
random effect
correlation structure
dahurianlarch
