منابع مشابه
Efficient Importance Sampling for Binary Contingency Tables
Importance sampling has been reported to produce algorithms with excellent empirical performance in counting problems. However, the theoretical support for its efficiency in these applications has been very limited. In this paper, we propose a methodology that can be used to design efficient importance sampling algorithms for counting and test their efficiency rigorously. We apply our technique...
متن کاملSampling contingency tables
Given positive integers r1; r2; : : : rm and c1; c2; : : : cn, let I(r; c) be the set ofm n arrays with nonnegative integer entries and row sums r1; r2; : : : rm respectively and column sums c1; c2; : : : cn respectively. Elements of I(r; c) are called contingency tables with these row and column sums. We consider two related problems on contingency tables. Given r1; r2; : : : rm and c1; c2; : ...
متن کاملImproved Bounds for Sampling Contingency Tables
We study the problem of sampling contingency tables (nonnegative integer matrices with specified row and column sums) uniformly at random. We give an algorithm which runs in polynomial time provided that the row sums ri and the column sums cj satisfy ri (n 3/ m log m), and cj (m 3/ n log n). This algorithm is based on a reduction to continuous sampling from a convex set. The same approach was t...
متن کاملLattice Points, Contingency Tables, and Sampling
Markov chains and sequential importance sampling (SIS) are described as two leading sampling methods for Monte Carlo computations in exact conditional inference on discrete data in contingency tables. Examples are explained from genotype data analysis, graphical models, and logistic regression. A new Markov chain and implementation of SIS are described for logistic regression.
متن کاملCharacterizing Optimal Sampling of Binary Contingency Tables via the Configuration Model
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 cond...
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ژورنال
عنوان ژورنال: Computing in Science & Engineering
سال: 2008
ISSN: 1521-9615
DOI: 10.1109/mcse.2008.62