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Sampling bias in systems with structural heterogeneity and limited internal diffusion

Abstract:

Complex-systems research is becomingly increasingly data-driven, particularly in the social and biological domains. Many of the systems from which sample data are collected feature structural heterogeneity at the mesoscopic scale (i.e. communities) and limited inter-community diffusion. Here we show that the interplay between these two features can yield a significant bias in the global characteristics inferred from the data. We present a general framework to quantify this bias, and derive an...

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Publication date:
2009-01-01
UUID:
uuid:c81b7b36-f820-461a-be89-2b8e2e6dae8b
Local pid:
oai:eureka.sbs.ox.ac.uk:243
Deposit date:
2011-05-19

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