Year: 2025
Type: preprint
Abstract: This paper investigates the nonparametric estimation of a circular regression function in an errors-in-variables framework. Two settings are studied, depending on whether the covariates are circular or linear. Adaptive estimators are constructed and their theoretical performance is assessed through convergence rates over Sobolev and Hölder smoothness classes. Numerical experiments on simulated and real datasets illustrate the practical relevance of the methodology.
Source: arXiv (Cornell University)
Authors: Nguyen, Tien Dat, Ngoc, Thanh Mai Pham
Institution: Laboratoire Analyse, Géométrie et Applications
Language: English
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4415329216
Cites:
Cited by:
Related to: