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逻辑回归异常值检验：条件方法AI 解读

We consider exact conditional methods for identifying outliers in logistic regression data. Tests for a single outlier and multiple outliers are developed assuming a logistic slippage model. The p-values for these tests are determined using an explicit enumeration of all possible responses consistent with the observed value of the sufficient statistic. Justifications are given for preferring this computationally intensive approach to standard methods based on asymptotic…

基于模型的统计学的一般框架AI 解读

This paper presents a general framework for model-based statistics. The framework is based on extended concepts of sufficiency and ancillarity. The fundamental theorem of the new theory exhibits in a single equation the reference distributions for decision theory, model checking, and conditional inference for a general statistical model. The theorem includes the equations upon which Bayesian and frequentist statistics are founded. The general theory also fills two gaps…

逻辑回归离群值检验的条件方法AI 解读

We consider exact conditional methods for identifying outliers in logistic regression data. Tests for a single outlier and multiple outliers are developed assuming a logistic slippage model. The p-values for these tests are determined using an explicit enumeration of all possible responses consistent with the observed value of the sufficient statistic. Justifications are given for preferring this computationally intensive approach to standard methods based on asymptotic…