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UID:1808@i2m.univ-amu.fr
DTSTART;TZID=Europe/Paris:20170612T153000
DTEND;TZID=Europe/Paris:20170612T163000
DTSTAMP:20170528T133000Z
URL:https://www.i2m.univ-amu.fr/evenements/kernel-spatial-regression-estim
 ation-for-non-stationary-process-with-applications/
SUMMARY: (...): Kernel spatial regression estimation for non-stationary pro
 cess with applications
DESCRIPTION:: Let ( Z i \, i ∈ Z N ) be a spatial process where Z i = ( X
  i \, Y i ) are such the Y i 's are real-valued and integrable variable an
 d X i 's are valued in a (semi-)metric separable space ( E \,d ). This wor
 k deals with the problem of the estimation the regression function\, r def
 ined by r( x ) =E( Y i | X i =x ) when the process ( Z i ) is not strictly
  stationary. We study the asymptotic behavior of the kernel estimator unde
 r mixing and local stationarity conditions.   We also discuss the theoreti
 cal and practical aspects of relaxing the stationary hypothesis and presen
 t some applications.-https://www.researchgate.net/profile/Anne_Francoise_Y
 ao-Portrait vidéo--
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