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通过生成函数计算置换分布及离散数据敏感性分析AI 解读

Generating functions provide a simple and elegant way to describe probability or frequency distributions of discrete statistics and, in particular, permutation distributions. They are also a computational tool. Many efficient algorithms, including those described as fast Fourier transform methods, network methods, and multiple shift methods, are different implementations of the recursions needed to evaluate generating functions efficiently. Our goals here are twofold. First,…

生成函数计算置换分布及离散数据敏感性分析AI 解读

Generating functions provide a simple and elegant way to describe probability or frequency distributions of discrete statistics and, in particular, permutation distributions. They are also a computational tool. Many efficient algorithms, including those described as fast Fourier transform methods, network methods, and multiple shift methods, are different implementations of the recursions needed to evaluate generating functions efficiently. Our goals here are twofold. First,…

精确拟合优度检验的方法AI 解读

Numerous goodness-of-fit tests with asymptotic chi-squared distributions have been proposed for discrete multivariate data, and there has been much discussion about using asymptotic results for computing critical values when there are small expected cell values. Although exact methods would be preferred in these situations, it generally is believed that such methods are computationally intractable. We propose methods for calculating exact distributions and significance…

含大小单元格计数的列联表分析方法AI 解读

The traditional practice has been to analyze contingency tables using asymptotic χ2 approximations for the tail probability of certain test statistics even when the approximation is known to be poor. For two-dimensional tables Pearson's X 2 statistic is most commonly used, whereas for multidimensional tables the likelihood ratio test is preferred because it makes it easy to test series of nested hypotheses. When asymptotic approximations are not adequate, exact tests are…

含大、小单元格计数的列联表分析方法AI 解读

The traditional practice has been to analyze contingency tables using asymptotic χ2 approximations for the tail probability of certain test statistics even when the approximation is known to be poor. For two-dimensional tables Pearson's X 2 statistic is most commonly used, whereas for multidimensional tables the likelihood ratio test is preferred because it makes it easy to test series of nested hypotheses. When asymptotic approximations are not adequate, exact tests are…