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The Gompertz Type Stochastic Growth Law and a Tree Diameter Distribution

机译:Gompertz型随机生长规律和树径分布

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摘要

The study presents a comprehensive stand-level model for the tree diameter distribution. A Gompertz type stochastic logistic growth law is used for describing diameter distribution. Using the Gompertz type stochastic law of tree diameter growth, the age and height dependent probability density function of diameter distribution is obtained. The mean age-diameter, height-diameter growth trends and their variances for the Gompertz type stochastic differential equation are derived. The expected tree diameter distribution is predicted by using the Fokker-Plank equation and stand measurements. The estimates of parameters are performed by the V distance procedure. The Weibull, and negative exponential distributions are selected to study their performance to the observations. To evaluate the goodness-of-fit, the absolute discrepancy, Kolmogorov-Smirnov, and Reynolds error index statistics are adapted. In addition, for estimating the goodness-of-fit, the Chi-squared test, pseudo-residuals, and Shapiro-Francia statistic are arranged, and the normal quantile plot is described. To model the diameter distribution, as an illustrative experience, a real data set from repeated measurements on permanent sample plots of pine stands in Dubrava forest district is used. The results are implemented in the symbolic computational language MAPLE.
机译:这项研究提出了一个用于树径分布的综合标准模型。使用Gompertz型随机逻辑增长定律描述直径分布。利用果树直径增长的Gompertz型随机律,获得了年龄和高度相关的直径分布的概率密度函数。推导了Gompertz型随机微分方程的平均年龄,身高和直径的增长趋势。预期的树木直径分布通过使用Fokker-Plank方程和林分测量值进行预测。参数的估计通过V距离过程执行。选择威布尔分布和负指数分布来研究它们对观测结果的性能。为了评估拟合优度,对绝对差异,Kolmogorov-Smirnov和雷诺误差指数统计量进行了调整。另外,为了估计拟合优度,布置了卡方检验,伪残差和Shapiro-Francia统计量,并描述了正常分位数图。为了对直径分布进行建模,作为一个说明性的经验,使用了对Dubrava林区松树林的永久样本样地进行重复测量得到的真实数据集。结果以符号计算语言MAPLE实现。

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