Random sampling of contingency tables via probabilistic divide-and-conquer

Stephen DeSalvo () and James Zhao
Additional contact information
Stephen DeSalvo: UCLA Department of Mathematics
James Zhao: USC Department of Mathematics

Computational Statistics, 2020, vol. 35, issue 2, No 19, 837-869

Abstract: Abstract We present a new approach for random sampling of contingency tables of any size and constraints based on a recently introduced probabilistic divide-and-conquer (PDC) technique. Our first application is a recursive PDC: it samples the least significant bit of each entry in the table, motivated by the fact that the bits of a geometric random variable are independent. The second application is via PDC deterministic second half, where one divides the sample space into two pieces, one of which is deterministic conditional on the other; this approach is highlighted via an exact sampling algorithm in the $$2\times n$$2×n case. Finally, we also present a generalization to the sampling algorithm where each entry of the table has a specified marginal distribution.

Keywords: Exact sampling; Approximate sampling; Transportation polytope; Boltzmann sampler (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s00180-019-00899-7 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:compst:v:35:y:2020:i:2:d:10.1007_s00180-019-00899-7

Ordering information: This journal article can be ordered from
http://www.springer.com/statistics/journal/180/PS2

DOI: 10.1007/s00180-019-00899-7

Access Statistics for this article

Computational Statistics is currently edited by Wataru Sakamoto, Ricardo Cao and Jürgen Symanzik

More articles in Computational Statistics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().