使用改进的威布尔分布参数化网络图的异质性。

IF 1.3 Q3 COMPUTER SCIENCE, THEORY & METHODS Applied Network Science Pub Date : 2023-01-01 DOI:10.1007/s41109-023-00544-9
Sinan A Ozbay, Maximilian M Nguyen
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引用次数: 3

摘要

我们提出了一种简单的方法,用单个参数σ来定量地捕捉网络图度分布的异质性。利用威布尔分布形状参数的指数变换,该控制参数允许在单位区间上的高度对称分布和高度非均匀分布之间容易地插值度分布。异质性的参数化也恢复了其他几种典型分布作为中间的特殊情况,包括高斯分布、瑞利分布和指数分布。然后,我们概述了一种通用的图形生成算法,以生成具有所需异质性的图形。通过与流行病学建模和光谱分析有关的例子,证明了这种异质性参数公式的实用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Parameterizing network graph heterogeneity using a modified Weibull distribution.

We present a simple method to quantitatively capture the heterogeneity in the degree distribution of a network graph using a single parameter σ . Using an exponential transformation of the shape parameter of the Weibull distribution, this control parameter allows the degree distribution to be easily interpolated between highly symmetric and highly heterogeneous distributions on the unit interval. This parameterization of heterogeneity also recovers several other canonical distributions as intermediate special cases, including the Gaussian, Rayleigh, and exponential distributions. We then outline a general graph generation algorithm to produce graphs with a desired amount of heterogeneity. The utility of this formulation of a heterogeneity parameter is demonstrated with examples relating to epidemiological modeling and spectral analysis.

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来源期刊
Applied Network Science
Applied Network Science Multidisciplinary-Multidisciplinary
CiteScore
4.60
自引率
4.50%
发文量
74
审稿时长
5 weeks
期刊最新文献
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