Monotonicity-constrained species distribution models
Monotonicity-constrained species distribution models
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DOI：
10.1890/10-2276.1
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发表时间：
2011-10-01
期刊：
影响因子：
4.8
通讯作者：
Hothorn, Torsten
中科院分区：
文献类型：
--
作者：
Hofner, Benjamin;Mueller, Joerg;Hothorn, Torsten
基于广义加性模型的物种分布模型的灵活建模框架，允许平滑，非线性效应和相互作用在生态学中越来越重要。通常，这种平滑函数估计的灵活性是通过惩罚估计过程来控制的。然而，实际形状仍然不明。在许多应用中，这是不可取的，因为研究人员对估计效果的形状有先验假设，其中单调性是最重要的。在这里，我们展示了如何单调性约束可以纳入最近提出的灵活的框架物种分布模型。我们的提案允许使用额外的不对称L-2惩罚对平滑效应和有序、分类变量施加单调性约束。使用R包mboost中实现的灵活boosting框架进行红鸢（Milvus milvus）育种的模型估计和变量选择。
Flexible modeling frameworks for species distribution models based on generalized additive models that allow for smooth, nonlinear effects and interactions are of increasing importance in ecology. Commonly, the flexibility of such smooth function estimates is controlled by means of penalized estimation procedures. However, the actual shape remains unspecified. In many applications, this is not desirable as researchers have a priori assumptions on the shape of the estimated effects, with monotonicity being the most important. Here we demonstrate how monotonicity constraints can be incorporated in a recently proposed flexible framework for species distribution models. Our proposal allows monotonicity constraints to be imposed on smooth effects and on ordinal, categorical variables using an additional asymmetric L-2 penalty. Model estimation and variable selection for Red Kite (Milvus milvus) breeding was conducted using the flexible boosting framework implemented in R package mboost.