An approximation algorithm for counting contingency tables
Abstract
We present a randomized approximation algorithm for counting contingency tables, mxn non-negative integer matrices with given row sums R=(r1, ..., rm) and column sums C=(c1, ..., cn). We define smooth margins (R,C) in terms of the typical table and prove that for such margins the algorithm has quasi-polynomial NO(ln N) complexity, where N=r1+...+rm=c1+...+cn. Various classes of margins are smooth, e.g., when m=O(n), n=O(m) and the ratios between the largest and the smallest row sums as well as between the largest and the smallest column sums are strictly smaller than the golden ratio (1+sqrt5)/2 = 1.618. The algorithm builds on Monte Carlo integration and sampling algorithms for log-concave densities, the matrix scaling algorithm, the permanent approximation algorithm, and an integral representation for the number of contingency tables.