Abstract
In this paper, we explore a novel regression problem encompassing both Euclidean and non-Euclidean predictors, all of which are subject to measurement errors. Specifically, we focus on a non-Euclidean predictor taking values in a compact and connected Lie group. We propose a nonparametric estimator and establish its asymptotic properties, including rates of convergence and an asymptotic distribution. We validate the practical efficacy of our estimator through simulation studies and real data analysis.
Disclosure statement
No potential conflict of interest was reported by the author(s).