An Examination of Using EWMA Charts for Monitoring United States Geospatial Data

Presentation Type

Oral and/or Visual Presentation

Presenter Major(s)

Statistics

Mentor Information

Paul Stephenson, stephenp@gvsu.edu

Department

Statistics

Location

Kirkhof Center 2259

Start Date

13-4-2011 2:00 PM

End Date

13-4-2011 2:30 PM

Keywords

Health and Wellness, Health, Illness, and Healing, Mathematical Science, Technology

Abstract

Geographic Information Systems (GIS) are a very helpful tool used to accumulate and present data. Although they are useful in displaying patterns and making inference about them, they can be misleading without the proper statistical methods. The authors will examine how Moran's I statistic changes for patterns of increasing spatial depression. They will also demonstrate how to create an "Exponentially Weighted Moving Average" (EWMA) control chart for global spatial statistics and monitor these charts over time. In the event that a control chart signals [WHAT?], one can then examine the local spatial statistics to determine the source of the signal. In an effort to examine the power associated with these monitoring procedures, the authors will also simulate the effect of an increase in one, two or three regions in the United States. The results of these simulations will be used to characterize the effects of shifts in the spatial dispersion across the United States.

This document is currently not available here.

Share

COinS
 
Apr 13th, 2:00 PM Apr 13th, 2:30 PM

An Examination of Using EWMA Charts for Monitoring United States Geospatial Data

Kirkhof Center 2259

Geographic Information Systems (GIS) are a very helpful tool used to accumulate and present data. Although they are useful in displaying patterns and making inference about them, they can be misleading without the proper statistical methods. The authors will examine how Moran's I statistic changes for patterns of increasing spatial depression. They will also demonstrate how to create an "Exponentially Weighted Moving Average" (EWMA) control chart for global spatial statistics and monitor these charts over time. In the event that a control chart signals [WHAT?], one can then examine the local spatial statistics to determine the source of the signal. In an effort to examine the power associated with these monitoring procedures, the authors will also simulate the effect of an increase in one, two or three regions in the United States. The results of these simulations will be used to characterize the effects of shifts in the spatial dispersion across the United States.