Blanchet, J., & Stauffer, A. (2013). Characterizing optimal sampling of binary contingency tables via the configuration model. Random Structures & Algorithms, 42(2), 159-184. https://doi.org/10.1002/rsa.20403

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Abstract

A binary contingency table is an m× n array of binary entries with row sums r=(r1,…, rm) and column sums c=(c1,…, cn). The configuration model generates a contingency table by considering ri tokens of type 1 for each row i and cj tokens of type 2 for each column j, and then taking a uniformly random pairing between type‐1 and type‐2 tokens. We give a necessary and sufficient condition so that the probability that the configuration model outputs a binary contingency table remains bounded away from 0 as article mathrsfs amsmath empty N= i= 1^ m r_i= j= 1^ n c_j goes to∞. Our finding shows surprising differences from recent results for binary symmetric contingency tables.© 2012 Wiley Periodicals, Inc. Random Struct. Alg., 2012

Authors
Jose Blanchet, Alexandre Stauffer
Publication date
2013/3
Journal
Random Structures & Algorithms
Volume
42
Issue
2
Pages
159-184
Publisher
Wiley Subscription Services, Inc., A Wiley Company