摘要 1. Hutchinson's n dimensional hypervolume concept

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論文資訊

• 類型：已發表論文
• 日期：2017-08-10

摘要

1. Hutchinson's n-dimensional hypervolume concept underlies many applications in contemporary 生態學 and 演化ary biology. Estimating hypervolumes from sampled data has been an ongoing challenge due to conceptual and 計算 issues. 2. We present new algorithms for delineating the boundaries and probability density within n-dimensional hypervolumes. The methods produce smooth boundaries that can fit data either more loosely (Gaussian kernel density estimation) or more tightly (one-classification via support vector machine). Further, the algorithms can accept abundance-weighted data, and the resulting hypervolumes can be given a probabilistic interpretation and projected into geographic space. 3. We demonstrate the properties of these methods on a large dataset that characterises the functional traits

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