Department of Statistics Seminar
North Carolina State University

presents

Jacqueline M. Hughes-Oliver

North Carolina State University

"Parametric Covariance Models for Shock-Induced Stochastic Processes"

ABSTRACT

A common assumption in modeling stochastic processes is that of weak stationarity. Although this is a convenient and sometimes justifiable assumption for many applications, there are other applications for which it is clearly inappropriate. One such application occurs when the process is driven by action at a limited number of sites, or point sources. Interest may lie not only in predicting the process, but also in assessing the effect of the point sources. In this seminar I present a general parametric approach of accounting for the effect of point sources in the covariance model of a stochastic process, and I discuss properties of a particular family from this general class. A simulation study demonstrates the performance of parameter estimation using this model, and the predictive ability of this model is shown to be better than some commonly used modeling approaches. Application to a dataset of electromagnetism measurements in a field containing a metal pole shows the advantages of our parametric nonstationary covariance models.

Friday, November 13, 1998

3:35 - 4:35 pm

206 Cox Hall

Refreshments will be served on the second floor of Dabney Hall (left of Room 222) at 3:00 pm.