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多项分布贝叶斯因子的下界及其在卡方拟合检验中的应用AI 解读

Lower bounds on Bayes factors in favor of the null hypothesis in multinomial tests of point null hypotheses are developed. These are then applied to derive lower bounds on Bayes factors in both exact and asymptotic chi-squared testing situations. The general conclusion is that the lower bounds tend to be substantially larger than $P$-values, raising serious questions concerning the routine use of moderately small $P$-values (e.g., 0.05) to represent significant evidence…

区间原假设的贝叶斯因子下界AI 解读

Expressions are derived for lower bounds on Bayes factors for interval null hypotheses. These are then studied for varying interval lengths and are related to two interesting results—one for point null hypotheses and another for one-sided hypotheses. These results are illustrated with two of the most frequently used hypothesis tests—the normal test and Student's t test.

区间原假设贝叶斯因子的下界AI 解读

Expressions are derived for lower bounds on Bayes factors for interval null hypotheses. These are then studied for varying interval lengths and are related to two interesting results—one for point null hypotheses and another for one-sided hypotheses. These results are illustrated with two of the most frequently used hypothesis tests—the normal test and Student's t test.