Manifold functional multiple regression model with LRD error term

Fuente: arXiv
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Auteurs principaux: Ovalle-Muñoz, Diana P., Ruiz-Medina, M. Dolores
Format: Preprint
Publié: 2024
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author Ovalle-Muñoz, Diana P.
Ruiz-Medina, M. Dolores
author_facet Ovalle-Muñoz, Diana P.
Ruiz-Medina, M. Dolores
contents This paper considers the problem of manifold functional multiple regression with functional response, time--varying scalar regressors, and functional error term displaying Long Range Dependence (LRD) in time. Specifically, the error term is given by a manifold multifractionally integrated functional time series (see, e.g., Ovalle--Muñoz \& Ruiz--Medina, 2024)). The manifold is defined by a connected and compact two--point homogeneous space. The functional regression parameters have support in the manifold. The Generalized Least--Squares (GLS) estimator of the vector functional regression parameter is computed, and its asymptotic properties are analyzed under a totally specified and misspecified model scenario. A multiscale residual correlation analysis in the simulation study undertaken illustrates the empirical distributional properties of the errors at different spherical resolution levels.
format Preprint
id arxiv_https___arxiv_org_abs_2402_08569
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Manifold functional multiple regression model with LRD error term
Ovalle-Muñoz, Diana P.
Ruiz-Medina, M. Dolores
Statistics Theory
60G10, 60G12, 60G18, 60G20, 60G22 (primary) 60G60
This paper considers the problem of manifold functional multiple regression with functional response, time--varying scalar regressors, and functional error term displaying Long Range Dependence (LRD) in time. Specifically, the error term is given by a manifold multifractionally integrated functional time series (see, e.g., Ovalle--Muñoz \& Ruiz--Medina, 2024)). The manifold is defined by a connected and compact two--point homogeneous space. The functional regression parameters have support in the manifold. The Generalized Least--Squares (GLS) estimator of the vector functional regression parameter is computed, and its asymptotic properties are analyzed under a totally specified and misspecified model scenario. A multiscale residual correlation analysis in the simulation study undertaken illustrates the empirical distributional properties of the errors at different spherical resolution levels.
title Manifold functional multiple regression model with LRD error term
topic Statistics Theory
60G10, 60G12, 60G18, 60G20, 60G22 (primary) 60G60
url https://arxiv.org/abs/2402.08569