TY - JOUR

T1 - Characterizing optimal sampling of binary contingency tables via the configuration model

AU - Blanchet, Jose

AU - Stauffer, A

PY - 2013/3/1

Y1 - 2013/3/1

N2 - 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 goes to ∞. Our finding shows surprising differences from recent results for binary symmetric contingency tables.

AB - 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 goes to ∞. Our finding shows surprising differences from recent results for binary symmetric contingency tables.

UR - http://www.scopus.com/inward/record.url?scp=84873082616&partnerID=8YFLogxK

UR - http://dx.doi.org/10.1002/rsa.20403

U2 - 10.1002/rsa.20403

DO - 10.1002/rsa.20403

M3 - Article

VL - 42

SP - 159

EP - 184

JO - Random Structures and Algorithms

JF - Random Structures and Algorithms

SN - 1042-9832

IS - 2

ER -