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Likelihood Ratio Methods for Monitoring Parameters of a Nested Random Effect Model
Lecture Notes-Monograph Series
Vol. 23, Change-Point Problems (1994), pp. 373-385
Published by: Institute of Mathematical Statistics
Stable URL: http://www.jstor.org/stable/4355786
Page Count: 13
You can always find the topics here!Topics: Statistical variance, Signals, Semiconductor wafers, Mathematical independent variables, False alarms, Parametric models, Modeling, Degrees of freedom, Manufacturing processes, Standard deviation
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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, 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 paper shows how to build a control system, based on Likelihood Ratio Tests, capable of controlling 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.
Lecture Notes-Monograph Series © 1994 Institute of Mathematical Statistics