Yuping Dong : Exponentially Weighted Moving Average Methods for Detection of Change Point for Event Rates

Posted by Weiya Zhang , part of the Statistics and Data Science Seminar.

At

April 14, 2006, 3:30 p.m.

In

SEO 512

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.