Statistics Discussion Group
Parker Hall 248
Fridays, 2 pm
Each time, a speaker will discuss something selected by the speaker. It is a good opportunity if you are interested in research in Statistics. You can check the full schedule by clicking here
Everyone is welcome.
Speaker: Ash Abebe
Title: Jaeckel-Hettmansperger-McKean Analysis of the Linear Model
Abstract: I will introduce the Jaeckel-Hettmansperger-McKean (JHM) approach of robust and efficient parameter estimation via minimization of rank-based pseudo-norms. JHM methods have been applied to estimation and testing problems ranging from simple location problems all the way to complex nonlinear regression problems. For location and one-way models, JHM approaches are equivalent to the rank-transformation methods Mann-Whitney-Wilcoxon and Kruskal-Wallis, respectively. However, the rank- transformation method does not extend nicely to models with interaction or linear models in general. My talk will cover JHM estimation in the linear model including a recent extension to hierarchical linear mixed models.
The last part of the talk is based on joint work with Yusuf Bilgic, John Kloke, and Joe McKean.
Speaker: Aaron McAtee
Title: Functional Linear Regression
Abstract: A look at functional linear regression when X(t) is a functional predictor and Y is a real valued response. I will review some methods for choosing the basis functions for the coefficient. A comparison of the various methods will be shown using Canadian weather data.
Speaker: Dr. Peng Zeng
Title: Principal Component Analysis for High-Dimensional Data
Abstract: Principal component analysis (PCA) is a popular procedure for dimension reduction. Targeting the application in high-dimensional data analysis, there are many novel developments on the theory and algorithms of PCA. In this talk, we will review some results in the recent literature.