Localisation

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Aix-Marseille Université
Institut de Mathématiques de Marseille (I2M) - UMR 7373
Site Saint-Charles : 3 place Victor Hugo, Case 19, 13331 Marseille Cedex 3
Site Luminy : Campus de Luminy - Case 907 - 13288 Marseille Cedex 9

Kernel spatial regression estimation for non-stationary process with applications




Date(s) : 12/06/2017   iCal
15h30 - 16h30

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 and X i ‘s are valued in a (semi-)metric separable space ( E ,d ). This work deals with the problem of the estimation the regression function, r defined 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 under mixing and local stationarity conditions. We also discuss the theoretical and practical aspects of relaxing the stationary hypothesis and present some applications.

https://www.researchgate.net/profile/Anne_Francoise_Yao

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