Hans-Georg Müller - UC Davis

Abstract

Random objects, i.e., random variables that take values in a separable metric space, pose many challenges for statistical analysis, since vector operations are not available in general metric spaces. Examples of random objects include distributions, covariance matrices and covariance surfaces, networks and other objects. The increasing ubiquity of samples of random objects has stimulated the development of metric statistics, a collection of statistical tools to characterize samples of such random objects and their relationships. For the geometric exploration of random objects we introduce depth profiles. For random objects in geodesic spaces, we propose transport regression, based on a transport algebra, where predictors and responses are transports. This presentation is based on joint work with Yaqing Chen, Paromita Dubey and Changbo Zhu.

Additional information:

• Speaker: Hans-Georg Müller
• Time: Monday, 11.07.2022, 16:00 - 17:00
• Location: Faculty Lounge, Room 0.036
• Further links:
  • Hans-Georg Müller's webpage
• Organizer: Statistics Group
• Contact:
  • Almut Lunkenheimer
  • +49 228 73 - 9228
  • ifs@uni-bonn.de