Professor; Ph.D., Carnegie Mellon, 1990.
Home Page: http://www.stat.osu.edu/~peruggia/
My research focuses on a combination of methodological and applied aspects. On the methodological front, my principal interests are in the areas of Bayesian modeling and Markov chain Monte Carlo estimation. I am especially interested in the development of numerical and graphical Bayesian techniques for exploratory data analysis, model building and selection, and in the related issue of constructing Bayesian diagnostics for assessing model fit and detecting the presence of outliers. With regard to estimation, I am interested in developing techniques for reducing the variability of estimators based on Markov chain Monte Carlo output and in the use of importance sampling techniques to accomplish modeling and diagnostic tasks. I am currently collaborating with Steve MacEachern, Subharup Guha, Thomas Santner, and Yu-Yun Ho (Telcordia Technologies) on various aspects of these research topics and the preparation of several papers. On the applied front, I am working on two major projects. The first is an NSF sponsored collaboration with Trisha Van Zandt in the OSU Department of Psychology. The focus of our project is the development of Bayesian models and methods for the analysis of response time data. The second applied project is a study of sleep apnea in children in collaboration with Paul Suratt (PI) et al. from the University of Virginia School of Medicine. (I am a consultant on this NIH funded project.). In addition to the work pertaining directly to the NIH project, we are also developing related, novel statistical methods to help to automate the analysis of sleep studies.