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A nonparametric on-line quality control procedure for vectorial observations

机译:矢量观测的非参数在线质量控制程序

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We consider an on-line nonparametric quality control procedure for multivariate observations. The goal of the procedure is to rapidly detect an out-of-control situation, that is, to detect a change in sampling distribution after a change point. Each successive observation creates a Voronoi cell indexed by the observation number. Suppose observation n + 1 falls into the Voronoi cell with index i, where i is from 1 to n. Then observation n + 1 has associated rank i. In the on-target situation these ranks are uniformly distributed but in the off-target situation these ranks tend to be large corresponding to the fact that the later off-target observations tend to clump together because later observations fall according to the off-target distribution. We use these ranks in a Cusum procedure. We found that we can approximately predict the on-target average run length (ARL) of our procedure and get reasonable off-target run lengths for any kind of structural break like a change of mean or a change of dispersion.
机译:我们考虑用于多变量观测的在线非参数质量控制程序。该程序的目标是快速检测失控情况,即检测变化点之后采样分布的变化。每个后续观察都会创建一个由观察编号索引的Voronoi细胞。假设观测值n + 1落入索引为i的Voronoi单元中,其中i从1到n。然后,观察值n + 1具有相关的等级i。在目标上的情况下,这些等级是均匀分布的,但是在目标外的情况下,这些等级往往较大,这对应于以下事实:后来的目标外的观察结果往往会聚在一起,因为后来的观察结果根据目标外的分布而下降。我们在Cusum程序中使用这些等级。我们发现,我们可以大致预测过程的目标平均游程长度(ARL),并针对任何类型的结构性断裂(例如均值变化或分散度变化)获得合理的目标外游程长度。

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