JournalsowrVol. 13, No. 3pp. 1821–1874

Statistics for Shape and Geometric Features

  • Dragi Anevski

    Lund University, Sweden
  • Christopher Genovese

    Carnegie Mellon University, Pittsburg, USA
  • Geurt Jongbloed

    Delft University of Technology, The Netherlands
  • Wolfgang Polonik

    University of California at Davis, USA
Statistics for Shape and Geometric Features cover
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Abstract

The constant emergence of novel technologies result in novel data generating devices and mechanisms that lead to a prevalence of highly complex data. To analyze such data, novel statistical methodologies need to be developed. This workshop addressed challenges that arise in the theoretical analyses of procedures in which geometry, shape and topology play central roles. The theoretical ideas involved here intersect deeply with a wide variety of fields, including mathematical statistics, probability theory, computational topology, and computational and differential geometry. The workshop brought together scholars with different perspectives, with the goal of facilitating cross-pollination to spur the development of new ideas, new analytical approaches, and new methods in geometric and shape statistics.

Cite this article

Dragi Anevski, Christopher Genovese, Geurt Jongbloed, Wolfgang Polonik, Statistics for Shape and Geometric Features. Oberwolfach Rep. 13 (2016), no. 3, pp. 1821–1874

DOI 10.4171/OWR/2016/32