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VERSION:2.0
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SUMMARY:Numerical methods for fractional stochastic PDEs with applications
  to spatial statistics
DTSTART:20191011T100000
DTEND:20191011T110000
DTSTAMP:20260407T144148Z
UID:2fad32a09b4bab52d7269c4ae7712b3ffd5264e1843e5c6bd1f86763
CATEGORIES:Conferences - Seminars
DESCRIPTION:Kristin KIRCHNER\nMany models in spatial statistics are based 
 on Gaussian Matérn fields. Motivated by the relation between this class o
 f Gaussian random fields and stochastic partial differential equations (PD
 Es)\, we consider the numerical solution of fractional-order elliptic stoc
 hastic PDEs with additive spatial white noise on a bounded Euclidean domai
 n.\n\n \n\nWe propose an approximation supported by a rigorous error anal
 ysis which shows different notions of convergence explicit and sharp rates
 . We furthermore discuss the computational complexity of the proposed meth
 od. Finally\, we present several numerical experiments\, which attest the 
 theoretical outcomes\, as well as a statistical application where we use t
 he method for inference\, i.e.\, for parameter estimation given data\, and
  for spatial prediction
LOCATION:MA B1 524 https://plan.epfl.ch/?room==MA%20B1%20524
STATUS:CONFIRMED
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