Event Date
Speaker: Alexander Giessing, Acting Assistant Professor, Department of Statistics, University of Washington
Title: "Efficient Inference on high-dimensional linear models with missing outcomes"
Abstract: This talk is concerned with inference on the regression function of a high-dimensional linear model when outcomes are missing at random. We propose an estimator which combines a Lasso pilot estimate of the regression function with a bias correction term based on the weighted residuals of the Lasso regression. The weights depend on estimates of the missingness probabilities (propensity scores) and solve a convex optimization program that trades off bias and variance optimally. Provided that the propensity scores can be pointwise consistently estimated at in-sample data points, our proposed estimator for the regression function is asymptotically normal and semi-parametrically efficient among all asymptotically linear estimators. Furthermore, the proposed estimator keeps its asymptotic properties even if the propensity scores are estimated by modern machine learning techniques. We validate the finite-sample performance of the proposed estimator through comparative simulation studies and the real-world problem of inferring the stellar masses of galaxies in the Sloan Digital Sky Survey. This project is joint work with Yikun Zhang and Yen-Chi Chen.
Bio: Dr. Alexander Giessing is an Acting Assistant Professor in the Department of Statistics at the University of Washington and an incoming Assistant Professor in the Department of Statistics and Data Science at the National University of Singapore. He was a Postdoctoral Research Associated at Princeton University and received his Ph.D. in Statistics from University of Michigan in 2018. He is broadly interested inference on high-dimensional data. His most recent research interests include Gaussian and bootstrap approximations, analysis of incomplete data, semiparametric inference, and empirical process theory. His research is supported by the National Science Foundation.
Faculty Webpage (links to UW): https://stat.uw.edu/about-us/people/alexander-giessing
Seminar Date/Time: Thursday April 11, 2024 at 4:10pm
Location: MSB 1147 (Colloquium Room) - refreshments at 3:30pm in courtyard