A new method based on the rejection sampling for finding statistical tests is proposed. This method is conceptually intuitive, easy to implement, and applicable for arbitrary dimension. To illustrate its potential applicability, three distinct empirical examples are presented: (1) examine the differences between group means of correlated (repeated) or independent samples, (2) examine if a mean vector equals to a specific fixed vector, and (3) investigate if samples come from a specific population distribution. The simulation examples indicate that the new test has similar statistical power as uniformly the most powerful (unbiased) tests. Moreover, these examples demonstrate that the new test is a powerful goodness-of-fit test.

翻译：本文提出了一种基于拒绝抽样的新方法，用于寻找统计检验。该方法概念直观、易于实现，且适用于任意维度。为说明其潜在适用性，本文展示了三个不同的实证案例：(1) 检验相关（重复）样本或独立样本的组间均值差异；(2) 检验均值向量是否等于特定固定向量；(3) 探究样本是否来自特定总体分布。模拟实验表明，新检验方法的统计功效与一致最优势（无偏）检验相当。此外，这些案例证明新检验是一种高效的拟合优度检验方法。