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VERSION:2.0
PRODID:-//Iowa State University CALS LAS Web Team//sites.iastate.edu//EN
BEGIN:VEVENT
UID:20210706T130000-867-www.stat.iastate.edu
DTSTART:20210706T130000Z
SEQUENCE:0
TRANSP:OPAQUE
DTEND:20210706T140000Z
LOCATION:Zoom: https://iastate.zoom.us/j/93826977132?pwd=aVBtWGVvbm1wdkw1aE
 ZTOElMV3VEQT09
SUMMARY:Seminar: estimation and inference of quantile spatially varying coe
 fficient models over complicated domains
CLASS:PUBLIC
DESCRIPTION:Abstract:&nbsp\;Regression analysis is frequently used in the a
 nalyses of spatial data. In this paper\, we propose a flexible quantile sp
 atially varying coefficient model to assess how conditional quantiles of t
 he response depend on covariates\, allowing the coefficient function to va
 ry with the spatial locations. The model can be used to explore spatial no
 n-stationarity of a regression relationship for heterogeneous spatial data
  distributed over a domain of a complex or irregular shape. For model esti
 mation\, we propose a quantile regression method adopting the bivariate pe
 nalized spline technique to approximate the unknown functional coefficient
 s. Under some regularity conditions\, the L2 convergence of the proposed e
 stimator is established with an optimal convergence rate.\n\nMore informat
 ion at: https://www.stat.iastate.edu/event/2021/seminar-estimation-and-inf
 erence-quantile-spatially-varying-coefficient-models-over\n\nZoom: https:/
 /iastate.zoom.us/j/93826977132?pwd=aVBtWGVvbm1wdkw1aEZTOElMV3VEQT09
DTSTAMP:20260904T205641Z
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