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Simplified Implementation of the Windowing Method for Systematic and Random Yield Calculation

机译:系统和随机收益率计算的加窗方法的简化实现

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摘要

To separate systematic and random yield loss, common implementations of the windowing method use an unweighted fit of the Poisson model. By comparison to a properly weighted fit of the negative binomial model, we show that the unweighted fit of the Poisson model can give highly inaccurate results, especially in the presence of clustering. The unweighted fit of the Poisson model is shown to improve by reducing the number of points included, with the best results given by the very simplest form, which uses two points only.
机译:为了分离系统损失和随机产量损失,开窗方法的常见实现方式使用了Poisson模型的未加权拟合。通过与负二项式模型的适当加权拟合进行比较,我们表明,泊松模型的未加权拟合会给出非常不准确的结果,尤其是在存在聚类的情况下。通过减少包含的点数,可以证明Poisson模型的未加权拟合得以改善,而最简单的形式(仅使用两个点)可以提供最佳结果。

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