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Non-linear regression models to identify functional forms of deforestation

机译:非线性回归模型,以识别毁林功能形式

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Identification of limited number of factors shall provide comprehensive general understanding of deforestation at broad scale, as well as the projection for the future. Only two factors - human population and relief energy (difference of minimum altitude from the maximum in a sampled area) - were verified if they give sufficient elucidation of deforestation by a regression model, whose functional forms identified by linear combinations of dummy variables firstly explored with use of high-precision Japanese data. Likelihood with spatial dependency was derived and applied then to East-Asian data, with which our models systematically showed eminently good relative appropriateness to the real data.
机译:识别有限的因素应在广泛的规模中为森林砍伐提供全面的普遍了解,以及未来的投影。只有两个因素 - 人口和救济能量(从采样区域中最大的最大海拔差异) - 如果通过回归模型足以阐明砍伐森林砍伐,其功能形式首先探索了虚拟变量的线性组合鉴定使用高精度日语数据。衍生和应用空间依赖的可能性,然后向东亚洲数据提供,我们的模型系统地显示出真实数据的相对恰当的相对适当性。

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