Prediction of air pollutants PM10 by ARBX(1) processes
Applications
2024-02-12 v1 Methodology
Abstract
This work adopts a Banach-valued time series framework for component-wise estimation and prediction, from temporal correlated functional data, in presence of exogenous variables. The strong-consistency of the proposed functional estimator and associated plug-in predictor is formulated. The simulation study undertaken illustrates their large-sample size properties. Air pollutants PM10 curve forecasting, in the Haute-Normandie region (France), is addressed by implementation of the functional time series approach presented
Keywords
Cite
@article{arxiv.2402.06574,
title = {Prediction of air pollutants PM10 by ARBX(1) processes},
author = {Javier Álvarez-Liébana and M. Dolores Ruiz-Medina},
journal= {arXiv preprint arXiv:2402.06574},
year = {2024}
}