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含缺失数据列联表的最大似然估计与模型选择AI 解读

In many studies the values of one or more variables are missing for subsets of the original sample. This article focuses on the problem of obtaining maximum likelihood estimates (MLE) for the parameters of log-linear models under this type of incomplete data. The appropriate systems of equations are presented and the expectation-maximization (EM) algorithm (Dempster, Laird, and Rubin 1977) is suggested as one of the possible methods for solving them. The algorithm has…

多项分布与二维列联表中异常单元格的检测检验AI 解读

A test based on the maximum adjusted residual from multinomial models, namely, the M test, is proposed. Sharp bounds on its critical values are provided for the multinomial case, while for the two-way table we present conservative critical values. The new test can be used to test null hypotheses against one- or two-sided alternatives and to detect outliers simultaneously with the rejection of the null hypothesis. Under certain alternatives, the M test is asymptotically more…

对 Schlesselman 所提变换准则的评论AI 解读

In the two-way analysis of variance with replicates, Schlesselman (1973) proposed a criterion of transformation based on classical statistics for testing homoscedasticity and additivity. He compared his criterion (Z(γ)) for selecting a transformation with the maximum likelihood estimate of Box and Cox (1964), and found Z(γ) superior in selecting a “correct” transformation when tested on models with normal and Cauchy error terms. We report here corrections of some of the…

对Schlesselman所提变换准则的评论AI 解读

In the two-way analysis of variance with replicates, Schlesselman (1973) proposed a criterion of transformation based on classical statistics for testing homoscedasticity and additivity. He compared his criterion (Z(γ)) for selecting a transformation with the maximum likelihood estimate of Box and Cox (1964), and found Z(γ) superior in selecting a “correct” transformation when tested on models with normal and Cauchy error terms. We report here corrections of some of the…