Sequential rank CUSUMs for location and dispersion
Abstract
We develop CUSUMs based on sequential ranks of the observations to detect changes over
time in the location and dispersion of a distribution. The CUSUMs are distribution free in
the sense that the appropriate control limits do not depend on the form or any parameters of
the unknown underlying distribution. As such the CUSUMs are fully self starting. The inand out-of-control average run length properties of the CUSUMs are gauged qualitatively via
theory-based calculations and quantitatively by Monte Carlo simulation. The CUSUMS are
shown to perform very well when compared to some existing parametric and nonparametric
CUSUMS. Implementation of the CUSUMs is illustrated in an application based on real data
from an industrial environment
URI
http://hdl.handle.net/10394/32018https://journals.co.za/content/journal/10520/EJC-da63441af
https://hdl.handle.net/10520/EJC-da63441af