Paper Info
Title
Characterizing optimal sampling of binary contingency tables via the configuration model
Abstract
AbstractA 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\documentclass{article} \usepackage{mathrsfs} \usepackage{amsmath} \pagestyle{empty} \begin{document} \begin{align*}N=\sum_{i=1}^m r_i=\sum_{j=1}^n c_j\end{align*} \end{document}goes to ∞. Our finding shows surprising differences from recent results for binary symmetric contingency tables. © 2012 Wiley Periodicals, Inc. Random Struct. Alg., 2012
Year
DOI
Venue
2013
10.1002/rsa.20403
Periodicals
Keywords
DocType
Volume
contingency tables,configuration model,uniform sampling
Journal
42
Issue
ISSN
Citations 
2
1042-9832
2
PageRank 
References 
Authors
0.48
15
2
Name
Order
Citations
PageRank
Jose H. Blanchet110026.53
Alexandre O. Stauffer213011.34