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Dear Zachary,

The following is a remote connection only, but let me mention it anyway.
In Section 7 of
Snijders, T.A.B. & Nowicki, K., Estimation and prediction for stochastic
block models for graphs with latent block structure.
Journal of Classification, 14 (1997), 75 - 100.
a procedure is mentioned for classifying vertices into 2 groups ("colors"),
which is mentioned to be similar to CONCOV (note the V at the end).  For
the mentioned procedure, it is proven that if the model is a stochastic
block model with 2 colors for undirected graphs, then classification
("color recovery") is asymptotically perfect.
Perhaps the idea there can be used also to prove this type of
asymptotically perfect color recovery for CONCOV itself, and then also for

Tom A.B. Snijders
Professor of Statistics and Methodology, Dept of Sociology, University of
Emeritus Fellow, Nuffield College, University of Oxford

On Tue, Jan 22, 2019 at 4:56 PM Neal, Zachary <[log in to unmask]> wrote:

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> Poster:       "Neal, Zachary" <[log in to unmask]>
> Subject:      CONCOR
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> SOCNET Colleagues,=0D
> =0D
> Are there any published formal evaluations, mathematically-oriented
> discuss=
> ions, or methodological critiques of CONCOR (convergence of iterated
> correl=
> ation; Breiger, Boorman, & Arabie, 1975)? I can find plenty of empirical
> ap=
> plications, even recent ones, but I'm looking for any work validating or
> in=
> validating the approach.=0D
> =0D
> Thanks,=0D
> Zak=0D
> =0D
> =E2=80=93=E2=80=93=E2=80=93=0D
> Zachary Neal, PhD=0D
> Associate Professor, Michigan State University=0D
> Managing Editor, Journal of Urban Affairs
> Associate Editor, Evidence and Policy

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