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误分类二项数据中两总体概率比较的局部最优设计AI 解读

Optimal experimental designs are found for estimating the difference P1−P2 of two population probabilities, using measuring instruments possibly subject to known error rates. The available experiments considered are to measure, for i = 1 or 2, the outcome of a trial on the population i without error, or with error, or with error with the possibility of checking either positive or negative responses. Given that the cost per observation depends on which experiment is carried…

误分类二项数据中比较两个概率的局部最优设计AI 解读

Optimal experimental designs are found for estimating the difference P1−P2 of two population probabilities, using measuring instruments possibly subject to known error rates. The available experiments considered are to measure, for i = 1 or 2, the outcome of a trial on the population i without error, or with error, or with error with the possibility of checking either positive or negative responses. Given that the cost per observation depends on which experiment is carried…

截断回归斜率的非参数估计AI 解读

A nonparametric estimate $\beta^\ast$ is presented for the slope of a regression line $Y = \beta_0X + V$ subject to the truncation $Y \leq y_0$. This model is relevant to a cosmological controversy which concerns Hubble's Law in Astronomy. The estimate $\beta^\ast$ corresponds to the zero-crossing of a random function $S_n(\beta)$, which for each $\beta$ is a Mann-Whitney type of statistic designed to measure heterogeneity among the calculated residuals $Y - \beta X$. The…

噪声条件下大型总体中的个体识别AI 解读

A new approach is presented to the problem of determining whether an individual (the target) appears in a large file where individuals are identified by measurements subject to error. This approach attaches costs to searching and to missing the individual. It corresponds to testing a simple hypothesis, that the measurements on the target and an element in the library have a given joint distribution, against the alternative that they are independent. Certain measures of…

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