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原文連結
論文資訊
- 類型：已發表論文
- 日期：2014-02-20
摘要
Aim The Hutchinsonian hypervolume is the conceptual foundation for many lines of ecological and 演化ary inquiry, including functional morphology, comparative biology, community 生態學 and niche theory. However, extant methods to sample from hypervolumes or measure their geometry perform poorly on high-dimensional or holey datasets. Innovation We first highlight the conceptual and 計算 issues that have prevented a more direct approach to measuring hypervolumes. Next, we present a new multivariate kernel density estimation method that resolves many of these problems in an arbitrary number of dimensions. Main conclusions We show that our method (implemented as the 'hypervolume' R package) can match several extant methods for hypervolume geometry and 物種 distribution modelling. Tools to quantify high-
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