Sampling for Conditional Inference on Contingency Tables
提出了新的序贯重要性抽样方法，用于从给定边际的列联表中抽样，生成的表格接近均匀分布，可用于近似检验统计量的零分布并计算表格总数，在多个实例中优于其他方法。
We propose new sequential importance sampling methods for sampling contingency tables with given margins. The proposal for each method is based on asymptotic approximations to the number of tables with fixed margins. These methods generate tables that are very close to the uniform distribution. The tables, along with their importance weights, can be used to approximate the null distribution of test statistics and calculate the total number of tables. We apply the methods to a number of examples and demonstrate an improvement over other methods in a variety of real problems. Supplementary materials are available online.