Austin R. Brown


Lalonde, Trent

Committee Member

Shafie, Khalil

Committee Member

Martinez, Rutilio


Department of Applied Statistics and Research Methods


University of Northern Colorado

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Place of Publication

Greeley (Colo.)


University of Northern Colorado

Date Created



182 pages

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Born digital


In statistical process control applications, situations may arise in which several presumably identical processes or “streams” are desired to be simultaneously monitored. Such a monitoring scenario is commonly referred to as a “Multiple Stream Process (MSP).” Charts which have been designed to monitor an MSP typically monitor the means of the streams through collecting samples from each stream and calculating some function of the sample means. The resulting statistic is then iteratively compared to control limits to determine if a single stream or subset of streams may have shifted away from a specified target value. Traditional MSP charting techniques rely on the assumption of normality, which may or may not be met in practice. Thus, a cumulative summation nonparametric MSP control charting technique, based on a modification of the classical extended median test was developed and is referred to as the “Nonparametric Extended Median Test – Cumulative Summation (NEMT-CUSUM) chart.” The development of control limits and estimation of statistical power are given. Through simulation, the NEMT-CUSUM is shown to perform consistently in the presence of normal and non-normal data. Moreover, it is shown to perform more optimally than parametric alternatives in certain circumstances. Results suggest the NEMT-CUSUM may be an attractive alternative to existing parametric MSP monitoring techniques in the case when distributional assumptions about the underlying monitored process cannot reasonably be made.

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