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SUMMARY:Fair Scores for Multivariate Gaussian Forecasts
DTSTART;VALUE=DATE-TIME:20260422T140000Z
DTEND;VALUE=DATE-TIME:20260422T150000Z
DTSTAMP;VALUE=DATE-TIME:20260512T141600Z
UID:indico-event-2113@events.imath.kiev.ua
DESCRIPTION:Speakers: Baran  Sandor (University of Debrecen\, Hungary)\n\n
 In ensemble-based probabilistic weather forecasting\, it is often necessar
 y to verify multidimensional predictions using verification scores. Such m
 ultidimensional quantities can be\, for example\, values of a weather vari
 able taken at different locations\, a set of several weather quantities\, 
 or simply the two-dimensional wind vector. Assuming multivariate normality
  of the forecasts\, we determine the dependence of two different verificat
 ion measures on the ensemble size and provide their sample size-adjusted f
 air versions. We demonstrate the usefulness of the application of fair sco
 res using real weather forecasts and simulation studies\, also examining t
 heir robustness with respect to deviations from normality.\n\nhttps://even
 ts.imath.kiev.ua/event/2113/
LOCATION:https://knu-ua.zoom.us/j/89643295643?pwd=eTBZZSt0d0thZzFyaUhDUFNG
 TVE3QT09 (ONLINE)
URL:https://events.imath.kiev.ua/event/2113/
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