| Summary: | The main objective of this dissertation is the development of CUSUM procedures
based on signed and unsigned sequential ranks. These CUSUMs can be
applied to detect changes in the location or dispersion of a process. The signed
and unsigned sequential rank CUSUMs are distribution-free and robust against the
effect of outliers in the data. The only assumption that these CUSUMs require is
that the in-control distribution is symmetric around a known location parameter.
These procedures specifically do not require the existence of any higher order moments.
Another advantage of these CUSUMs is that Monte Carlo simulation can
readily be applied to deliver valid estimates of control limits, irrespective of what
the underlying distribution may be.
Other objectives of this dissertation include a brief discussion of the results
and refinements of the CUSUM in the literature. We justify the use of a signed
sequential rank statistic. Also, we evaluate the relative efficiency of the suggested
procedure numerically and provide three real-world applications from the engineering
and financial industries. === MSc (Risk Analysis), North-West University, Potchefstroom Campus, 2015
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