Nonparametric Regression Based on Discretely Sampled Curves

Authors

  • Liliana Forzani Universidad Nacional del Litoral
  • Ricardo Fraiman Centro de Matemática
  • Pamela Llop Universidad Nacional del Litoral

DOI:

https://doi.org/10.57805/revstat.v18i1.283

Keywords:

nonparametric regression , functional data, discrete curves

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.

Published

2020-02-18

How to Cite

Forzani , L., Fraiman , R., & Llop , P. (2020). Nonparametric Regression Based on Discretely Sampled Curves. REVSTAT-Statistical Journal, 18(1), 1–26. https://doi.org/10.57805/revstat.v18i1.283