We consider certain respondent-driven sampling procedures on dense and sparse graphs. Under the assumption that the sequence of the vertex-sets is ergodic we understand possible limiting graphs. In the dense regime they can be expressed in terms of the original dense graph via a transformation related to the invariant measure of the ergodic sequence. In the sparse regime by a specific clumping procedure of the sampled vertices we construct a sequence of sparse graphs which converge to the governing graphon in the cut-metric.
Uncertainty Quantification Seminar Prof. dr. Siva Athreya, Indian Stat. Inst.
Respondent-Driven Sampling and Random Graph Convergence
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        When
              
              
5 Feb 2019
 from 11 a.m.
    to 5 Feb 2019 noon
              CET (GMT+0100)
            
            
              Where
              F1.15 (Nikhef building, Sciencepark 105-107)
            
            
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