David Matteson

Overview

My primary research focus has involved the analysis of dependent, multivariate data and the development of accompanying statistical methodology. My research includes biological, environmental, financial, operational and sociological applications.

### Publications

#### Journal Articles

• D. R. Kowal, David Matteson, D. Ruppert. 2016. A Bayesian Multivariate Functional Dynamic Linear Model, Journal of the American Statistical Association .
• D. R. Kowal, David Matteson, D. Ruppert. 2016. Functional Autoregression for Sparsely Sampled Data, Journal of Business and Economic Statistics .
• David Matteson, Ruey S. Tsay. 2016. Independent Component Analysis via Distance Covariance, Journal of the American Statistical Association .
• Brad S Westgate, Dawn B Woodard, David Matteson, Shane G Henderson. 2016. Large-Network Travel Time Distribution Estimation, with Application to Ambulance Fleet Management, European Journal of Operational Research . 252(1):322-333.
• Benjamin B Risk, David Matteson, David Ruppert, R. Nathan Spreng. 2016. Spatiotemporal Mixed Modeling of Multi-subject fMRI via Method of Moments, Neuroimage . 142:280-292.
• William B Nicholson, David Matteson, J Bien. 2016. VARX-L: Structured Regularization for Large Vector Autoregressions with Exogenous Variables, International Journal of Forecasting .
• Tupper Laura, David Matteson, John Handley. 2016. Mixed Data and Classification of Transit Stops, 2016 IEEE International Conference on Big Data (Big Data) . 2225-2232.
• Zhengyi Zhou, David Matteson. 2016. Predicting Melbourne Ambulance Demand Using Kernel Warping, Annals of Applied Statistics . 10(4):1977-1996.
• Nicholas A James, Arun Kejariwal, David Matteson. 2016. Leveraging Cloud Data to Mitigate User Experience from Breaking Bad: The Twitter Approach, 2016 IEEE International Conference on Big Data (Big Data) . 3499-3508.
• Zhengyi Zhou, David Matteson. 2015. Predicting Spatio-Temporal Ambulance Demand: A Spatio-Temporal Kernel Approach, Proceedings of the 21st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD) . 2297-2303.
• Zhengyi Zhou, David Matteson, Dawn B Woodard, Shane G Henderson, Athanasios C Micheas. 2015. A Spatio-Temporal Point Process Model for Ambulance Demand, Journal of the American Statistical Association . 110(509):6-15.
• Benjamin B Risk, David Matteson, David Ruppert, Ani Eloyan, Brian Caffo. 2014. An Evaluation of Independent Component Analyses with an Application to Resting State fMRI, Biometrics . 70(1):224-236.
• W. A. Erickson, S. von Schrader, S. M. Bruyere, S. Van Looy, David Matteson. 2014. Disability-Inclusive Employer Practices and Hiring of Individuals with Disabilities, Rehabilitation Education . 28(4):309-328.
• Nicholas A James, David Matteson. 2014. ecp: An R Package for Nonparametric Multiple Change Point Analysis of Multivariate Data, Journal of Statistical Software . 62(7):1-25.
• David Matteson, Nicholas A James. 2014. A Nonparametric Approach for Multiple Change Point Analysis of Multivariate Data, Journal of the American Statistical Association . 109(505):334-345.
• David Matteson, Nicholas A James, William B Nicholson, Louis C Segalini. 2013. Locally Stationary Vector Processes and Adaptive Multivariate Modeling, Acoustics, Speech and Signal Processing, IEEE . 8722-8726.
• Brad S Westgate, Dawn B Woodard, David Matteson, Shane G Henderson. 2013. Travel Time Estimation for Emergency Vehicles using Bayesian Data Augmentation, Annals of Applied Statistics . 7(2):1139-1161.
• Scott H Holan, W H Yang, David Matteson, C K Wikle. 2012. An Approach for Identifying and Predicting Economic Recessions in Real-Time Using Time-Frequency Functional Models, Applied Stochastic Models in Business and Industry . 28(6):485-499.
• David Matteson, Ruey S. Tsay. 2011. Dynamic Orthogonal Components for Multivariate Time Series, Journal of the American Statistical Association . 106(496):1450-1463.
• Dawn B Woodard, David Matteson, Shane G Henderson . 2011. Establishing Stationarity of Count-Valued Time Series Models using Drift Conditions, Electronic Journal of Statistics . 5(0):800-828.
• David Matteson, Matthew W. McLean, Dawn B Woodard, Shane G Henderson. 2011. Forecasting Emergency Medical Service Call Arrival Rates, Annals of Applied Statistics . 5(2B):1379-1406.
• David Matteson, David Ruppert. 2011. GARCH Models of Dynamic Volatility and Correlation, IEEE Signal Processing Magazine . 28(5):72-82.

Textbooks

• David Ruppert, David Matteson. 2015. Statistics and Data Analysis for Financial Engineering. in Statistics and Data Analysis for Financial Engineering. New York, NY, United States: Springer, 2015. (721)

Book Chapters

• David Matteson, Nicholas James, William Nicholson. 2016. Statistical Measures of Dependence For Financial Data. in Financial Signal Processing and Machine Learning. John Wiley & Sons, 2016. A.N. Akansu, S.R. Kulkarni, D. Malioutov, I. Pollak.
• Zhengyi Zhou, David Matteson. 2016. Temporal and Spatio-Temporal Models for Ambulance Demand. in Healthcare Data Analysis. John Wiley & Sons, 2016.

Honors and Awards

• Best Paper Award, National Association of Rehabilitation Research and Training Centers Association. 2015
• Faculty Early Career Development (CAREER) Award, National Science Foundation. 2015
• Faculty Research Award, PARC/Xerox Foundation. 2014
• Best Academic Paper Award, R/Finance 2013, Applied Finance with R, International Center for Futures and Derivatives. 2013
• Best Academic Paper Award, R/Finance 2011, Applied Finance with R, International Center for Futures and Derivatives. 2011
• Paul Meier Fellowship, Department of Statistics, University of Chicago. 2008
• Statistical Consulting Award, Department of Statistics, University of Chicago. 2005

### Areas of Expertise

• Disability
• Econometrics
• Statistical Theory, Methods, Analysis