Kriging uncertainty for functional data: a comparison study
نویسندگان
چکیده
Uncertainty evaluation for spatial prediction of curves remains an open issue in the functional data literature. We consider three different approaches that rely on semi-parametric bootstrapping, principal component analysis and classical inference for additive models respectively.
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تاریخ انتشار 2014