Statistics and Data Science Seminar
Yuping Dong
(PhD Candidate in Statistics, MSCS, UIC)
Exponentially Weighted Moving Average Methods for Detection of Change Point for Event Rates
Abstract: The exponentially weighted moving average methods (EWMA) are one
of the statistical surveillance methods commonly studied in statistical
process control literature. The EWMA methods are mainly used to monitor
the mean of the distribution of a continuous quality measure. In this
talk, we present a way to extend the EWMA procedure to the case of a
positive shift in the incidence rate per exposure unit of a Poisson
process. Three types of EWMA methods, EWMAe, EWMAa1 and EWMAa2, are
constructed, all with an alarm statistic, which is an exponentially
weighted moving average of the observations per exposure unit. Analytical
bounds for different measures of evaluation, suitable in different types
of applications, are provided such as the expected delay, the average run
length to an alarm and the probability of successful detection, to give a
broad picture of the features of the methods. Results from a simulation
study are presented both for a fixed average run length to the first false
alarm and a fixed probability of a false alarm.
There will be tea starting at 3:15pm.
Friday April 14, 2006 at 3:30 PM in SEO 512