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 -