Asymptotics for Spherical Functional Autoregressions
Statistics Theory
2019-07-15 v1 Probability
Statistics Theory
Abstract
In this paper, we investigate a class of spherical functional autoregressive processes, and we discuss the estimation of the corresponding autoregressive kernels. In particular, we first establish a consistency result (in sup and mean-square norm), then a quantitative central limit theorem (in Wasserstein distance), and finally a weak convergence result, under more restrictive regularity conditions. Our results are validated by a small numerical investigation.
Cite
@article{arxiv.1907.05802,
title = {Asymptotics for Spherical Functional Autoregressions},
author = {Alessia Caponera and Domenico Marinucci},
journal= {arXiv preprint arXiv:1907.05802},
year = {2019}
}
Comments
40 pages, 8 figures