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SUMMARY:Nonparametric smoothing of directional and axial data - Lutz  Duem
 bgen (Universität Bern)
DTSTART:20250710T100000Z
DTEND:20250710T110000Z
UID:TALK234175@talks.cam.ac.uk
DESCRIPTION:We discuss generalized linear models for directional data wher
 e the conditional distribution of the response is a von Mises-Fisher distr
 ibution in arbitrary dimension or a Bingham distribution on the unit circl
 e. To do this properly\, we parametrize von Mises-Fisher distributions by 
 Euclidean parameters and investigate computational aspects of this paramet
 rization. Then we modify this approach for local polynomial regression as 
 a means of nonparametric smoothing of distributional data. The methods are
  illustrated with simulated data and a data set from planetary sciences in
 volving covariate vectors on a sphere with axial response.\nThis is joint 
 work with Caroline Haslebacher (SWRI\, Boulder\, USA).
LOCATION:Seminar Room 2\, Newton Institute
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