Results 271 to 280 of about 15,407,870 (296)
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2016
In the last chapter, a qualitative comparison of various real-world structures with classic random graph models revealed that complex networks are non-random in many aspects. This chapter focuses on the question of how to quantify the statistical significance of an observed network structure with respect to a given random graph model.
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In the last chapter, a qualitative comparison of various real-world structures with classic random graph models revealed that complex networks are non-random in many aspects. This chapter focuses on the question of how to quantify the statistical significance of an observed network structure with respect to a given random graph model.
openaire +1 more source
Null Model Analysis of Species Co-Occurrence Patterns
Ecology, 2000Nicholas J. Gotelli
exaly +2 more sources
The use and limitations of null-model-based hypothesis testing
Biology and Philosophy, 2020Mingjun Zhang
exaly
A guide to null models for animal social network analysis
Methods in Ecology and Evolution, 2017Damien R. Farine
exaly
Research frontiers in null model analysis
Global Ecology and Biogeography, 2001Nicholas J. Gotelli
exaly
Parallel Generation of Simple Null Graph Models
2020 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), 2020Jack Garbus +2 more
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