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首页> 外文期刊>Physica, A. Statistical mechanics and its applications >An analytic approach to the measurement of nestedness in bipartite networks
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An analytic approach to the measurement of nestedness in bipartite networks

机译:双向网络中嵌套度的一种分析方法

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We present all index that measures the nestedness pattern of bipartite networks, a problem that arises in theoretical ecology. Our measure is derived using the Sum of distances of the Occupied elements in the incidence matrix of the network. This index quantifies directly the deviation of a given matrix from the nested pattern. In the simplest case the distance of the matrix element a(i,j) is d(i,j) = i + j, the Manhattan distance. A generic distance is obtained as d(i,j) = (i(x) + j(x))(1/x). The nestedness index is defined by nu = 1 - tau, where tau is the "temperature" of the matrix. We construct the temperature index using two benchmarks: the distance of the complete nested matrix that corresponds to zero temperature and the distance of the average random matrix where the temperature is defined as one. We discuss all important feature of the problem: matrix Occupancy p. We address this question using a metric index X that adjusts for matrix Occupancy.
机译:我们提出了衡量二分网络嵌套模式的所有指标,这是理论生态学中出现的一个问题。我们的度量是使用网络入射矩阵中被占领元素的距离总和得出的。该索引直接量化给定矩阵与嵌套模式的偏差。在最简单的情况下,矩阵元素a(i,j)的距离为d(i,j)= i + j,即曼哈顿距离。通用距离为d(i,j)=(i(x)+ j(x))(1 / x)。嵌套指数由nu = 1-tau定义,其中tau是矩阵的“温度”。我们使用两个基准来构建温度指数:对应于零温度的完整嵌套矩阵的距离,以及将温度定义为1的平均随机矩阵的距离。我们讨论该问题的所有重要特征:矩阵占用率p。我们使用针对矩阵占用率进行调整的指标索引X来解决此问题。

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