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Two-Stage Controlled Fractional Factorial Screening for Simulation Experiments

机译:两阶段控制的分数阶因子筛选用于模拟实验

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Factor screening with statistica1control makes sense in the context of simulation experiments that have random error, but can be run automatically on a computer and thus can accommodate a large number of replications. The discrete-event simulations common in the operations research field are well suited to controlled screening. In this paper, two methods of factor screening with control of Type I error and power are compared. The two screening methods are both robust with respect to two-factor interactions and nonconstant variance. The first method is an established sequential method called controlled sequential bifurcation for interactions (CSB-X). The second method uses a fractional factorial design in combination with a two-stage procedure for controlling power. The two-stage controlled fractional factorial (TCFF) method requires less prior information and is more efficient when the percentage of important factors is 5% or higher.
机译:在具有随机误差的模拟实验中,使用statistica1control进行因子筛选是有意义的,但是可以在计算机上自动运行,因此可以容纳大量重复。运筹学领域中常见的离散事件模拟非常适合于受控筛选。本文比较了两种控制I型误差和功率的因素筛选方法。两种筛选方法在两因素交互作用和非恒定方差方面均很可靠。第一种方法是已建立的顺序方法,称为交互作用的受控顺序分叉(CSB-X)。第二种方法使用分数阶乘设计并结合两阶段控制功率的程序。两阶段控制分数阶乘(TCFF)方法需要较少的先验信息,并且当重要因子的百分比为5%或更高时,效率更高。

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