Reconstructing networks with unknown and heterogeneous errors Tiago P. Peixoto∗ Department of Mathematical Sciences and Centre for Networks and Collective Behaviour, University of Bath, Claverton Down, Bath BA2 7AY, United Kingdom and ISI Foundation, Via...
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Reconstructing networks with unknown and heterogeneous errors Tiago P. Peixoto∗ Department of Mathematical Sciences and Centre for Networks and Collective Behaviour, University of Bath, Claverton Down, Bath BA2 7AY, United Kingdom and ISI Foundation, Via Chisola 5, 10126 Torino, Italy The vast majority of network datasets contains errors and omissions, although this is rarely in- corporated in traditional network analysis. Recently, an increasing effort has been made to fill this methodological gap by developing network reconstruction approaches based on Bayesian inference. These approaches, however, rely on assumptions of uniform error rates and on direct estimations of the existence of each edge via repeated measurements, something that is currently unavailable for the majority of network data. Here we develop a Bayesian reconstruction approach that lifts these limitations by not only allowing for heterogeneous errors, but also for individual edge measurements without direct error es
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