Nonparametric regression based on discretely sampled curves
Statistics Theory
2017-05-29 v3 Statistics Theory
Abstract
In the context of nonparametric regression, we study conditions under which the consistency (and rates of convergence) of estimators built from discretely sampled curves can be derived from the consistency of estimators based on the unobserved whole trajectories. As a consequence, we derive asymptotic results for most of the regularization techniques used in functional data analysis, including smoothing and basis representation.
Cite
@article{arxiv.1604.08428,
title = {Nonparametric regression based on discretely sampled curves},
author = {Forzani Liliana and Fraiman Ricardo and Llop Pamela},
journal= {arXiv preprint arXiv:1604.08428},
year = {2017}
}