Likelihood Ratio Methods for Monitoring Parameters of a Nested Random Effect Model
针对嵌套随机效应模型中均值和方差成分的监控问题，提出基于似然比检验的控制系统，并与传统控制图比较，适用于集成电路制造等场景。
Abstract In many practical situations the variance of a set of measurements can be attributed to several known sources of variability. For example, if several measurements of each item of a lot are taken, then one may need to deal not only with the within-item variability, but also with item-to-item within-lot and lot-to-lot components of variability. In such cases conventional control charts tend to produce an unacceptably high rate of false alarms and in general represent a rather weak diagnostic tool. This article shows how to build a control system based on likelihood ratio tests capable of monitoring the mean and variance components of a nested random effect model. The strong points and weaknesses of this approach are compared to those of competing methods, and some examples related to manufacturing of integrated circuits are discussed.