Functional Data Analysis of Populations of Tree-structured Objects

ABSTRACT
This talk proposes a new method for understanding the structure of populations of complex objects in the area of medical image analysis. The new methods require invention of approaches to the statistical analysis of a population of tree-structured objects. The approach is based on a metric in tree space. The metric provides a foundation for defining a notion of population center. In Functional Data Analysis, variation about the center is usually analyzed by Principal Component Analysis. Here an analog of PCA is developed for tree space.

Refreshments will be served at 3:45 p.m. in Room 008 of the Statistics Building

College of Natural Sciences