论文检索

多因素实验中的交互作用检测AI 解读

Summary One of the main advantages of factorial experiments is the information that they can offer on interactions. When there are many factors to be studied, some or all of this information is often sacrificed to keep the size of an experiment economically feasible. Two strategies for group screening are presented for a large number of factors, over two stages of experimentation, with particular emphasis on the detection of interactions. One approach estimates only main…

区组设计中双重处理与单一处理的比较AI 解读

Experiments having two treatment factors and one blocking factor are considered in which a particular combination of treatment factor levels must be excluded. The motivation for the work is a medical trial of two drugs in which a double placebo cannot be administered on ethical grounds. The contrasts of interest compare the effects of having both treatment factors at nonzero labelled levels with the effects of having only one treatment factor at a nonzero labelled level. A…

区组设计中双处理与单处理的比较AI 解读

Experiments having two treatment factors and one blocking factor are considered in which a particular combination of treatment factor levels must be excluded. The motivation for the work is a medical trial of two drugs in which a double placebo cannot be administered on ethical grounds. The contrasts of interest compare the effects of having both treatment factors at nonzero labelled levels with the effects of having only one treatment factor at a nonzero labelled level. A…

二维点过程密度的稳健估计AI 解读

A method is proposed for obtaining estimators of the density of a two-dimensional point process which are reasonably unbiased for Poisson, square lattice and equilateral triangular lattice processes. A simple fairly robust estimator is discussed.

二维点过程密度的稳健估计AI 解读

A method is proposed for obtaining estimators of the density of a two-dimensional point process which are reasonably unbiased for Poisson, square lattice and equilateral triangular lattice processes. A simple fairly robust estimator is discussed.