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SUMMARY:Estimating a covariance function from fragments of functional data
  - Aurore Delaigle (University of Melbourne)
DTSTART:20180628T084500Z
DTEND:20180628T093000Z
UID:TALK107482@talks.cam.ac.uk
CONTACT:INI IT
DESCRIPTION:Functional data are often observed only partially\, in the for
 m of fragments. In that case\, the standard approaches for estimating the 
 covariance function do not work because entire parts of the domain are com
 pletely unobserved. In previous work\, Delaigle and Hall (2013\, 2016) hav
 e suggested ways of estimating the covariance function\, based for example
  on Markov assumptions. In this work we take a completely different approa
 ch which does not rely on such assumptions. We show that\, using a tensor 
 product approach\, it is possible to reconstruct the covariance function u
 sing observations located only on the diagonal of its domain.
LOCATION:Seminar Room 1\, Newton Institute
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