Thomas Severini
Professor of Statistics and Data Science
Ph.D., 1987, University of Chicago
- severini@northwestern.edu
- 2006 Sheridan Road, Room 305
Research Interests
My research focuses on likelihood-based statistical methods such as maximum likelihood estimation and tests and confidence regions based on the likelihood ratio statistic. My work in this area is concerned with higher-order asymptotic approximations to the distributions of likelihood-based statistics and the development of statistical methodology for models with many parameters, including applications in finance and econometrics. I am also interested in the application of statistical methods to the analysis of sports data.
Recent Publications
- Integrated Likelihood Functions for Non-Bayesian Inference, Biometrika, 94 (2007), pp. 529-542.
- Likelihood Ratio Statistics Based on an Integrated Likelihood, Biometrika, 97 (2010), pp. 481-96.
- Frequency Properties of Inferences Based on an Integrated Likelihood Function, Statistica Sinica 21 (2011), pp. 433-47.
- Efficiency bounds for estimating linear functionals of nonparametric regression models with endogenous regressors (with G. Tripathi), Journal of Econometrics, 170 (2012), pp. 491-8.
- A Flexible Approach to Inference in Semiparametric Regression Models with Correlated Errors using Gaussian Processes (with H. He), Computational Statistics and Data Analysis, 103 (2016), 316-29.
- A Nonparametric Approach to Measuring the Sensitivity of an Asset's Return to the Market, Annals of Finance, 12 (2016), 179-99.
- How jet lag impairs major league baseball performance (with A. Song and R. Allada), Proc. Nat. Acad. Science, 114 (2017), 1407-1412.
- Analytic Methods in Sports: Using Mathematics and Statistics to Understand Data from Baseball, Football, Basketball, and Other Sports, (2014), published by CRC Press.
- Introduction to Statistical Methods for Financial Models, (2017), published by CRC Press.