Fall 2023 Seminars

The Department of Statistics Seminar Series for the Fall 2023 semester will take place on Mondays at 3 PM EST. Events will be a mixture of in-person (with a remote viewing option) unless otherwise noted.

September 18, 2023 (via Zoom)

Phyllis Wan Assistant Professor at Erasmus University Rotterdam

Title: Graphical Lasso for Extremes

Abstract: Gaussian graphical lasso is a powerful tool for modeling sparse dependence structure for non-extreme data. For extreme data, Gaussian graphical model is not suitable. Instead, Huesler-Reiss graphical model was recently proposed as an alternative. The adaptation of graphical lasso in this scenario is not straightforward due to the different structure in parameter matrix. We propose a graphical lasso for Huesler-Reiss graphical model through a reparametrization. The estimator is solved via a penalized likelihood and enjoys convenient properties of the traditional graphical lasso: concentration equalities, fast computation and the ability to scale up to large dimensions.

September 11, 2023

Barry Nussbaum Adjunct Professor at University of Maryland Baltimore County

Title: It's Not What We Said, It's Not What They Heard, It's What They Say They Heard

Abstract: Statisticians have long known that success in our profession frequently depends on our ability to succinctly explain our results so decision makers may correctly integrate our efforts into their actions. However, this is no longer enough. While we still must make sure that we carefully present results and conclusions, the real difficulty is what the recipient thinks we just said. The situation becomes more challenging in the age of “big data”. This presentation will discuss what to do, and what not to do. Examples, including those used in court cases, executive documents, and material presented for the President of the United States, will illustrate the principles.