Álvarez Liébana, JavierRuiz Medina, María DoloresLangousis, Andreas2024-01-242024-01-242019Álvarez-Liébana J, Ruiz-Medina MD (2019) Prediction of air pollutants PM10 by ARBX(1) processes. Stoch Environ Res Risk Assess 33:1721–1736. https://doi.org/10.1007/s00477-019-01712-z10.1007/s00477-019-01712-zhttps://hdl.handle.net/20.500.14352/95035This 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.engAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/journal article1436-3259https://doi.org/10.1007/s00477-019-01712-zhttps://link.springer.com/article/10.1007/s00477-019-01712-zhttps://link.springer.com/journal/477restricted access512.642551.5519.246.8Air pollutants forecastingBanach spacesFunctional time seriesMeteorological variablesStrong consistencyAnálisis funcional y teoría de operadoresMeteorología (Física)1202 Análisis y Análisis Funcional2509 Meteorología