Dynamic Functional Regression Models

University Of Wisconsin-Milwaukee, Milwaukee WI

Investigators

Abstract

The analysis of samples of curves is a field of growing relevance in statistics. Samples of curves arise when a time-dependent process is observed on a group of individuals. Such curves present both time and amplitude variability ("horizontal" and "vertical" variability), and both types of variation have to be statistically modeled in order to draw valid inference from the data. The investigator is developing dynamic regression models, that is, models for prediction of response curves based on explanatory curves, that explicitly take into account time variability. The properties of these methods are being studied theoretically, by simulation, and by the analysis of real-life data sets. Computer software implementing these methods is also being developed. Data consisting of samples of curves include, among many others, human growth curves, time-dependent gene expression profiles, daily air pollutant concentrations, and stock prices. The investigator's work will help scientists work on a broad range of applications and these statistical techniques will help provide new insights into scientific areas as diverse as medicine, genetics, environmental studies, and economics.