Nonparametric time series prediction: A semi-functional partial linear modeling

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Functional time series approach for forecasting very short-term electricity demand (2013, result): “The idea of forming a TS of curves from a seasonal univariate TS is not new and has been considered by several authors, including Aneiros-Pérez and Vieu [1] and Besse et al.”
Forecasting: theory and practice (2020, methodology): “tric perspective, Besse et al. (2000) proposed a functional kernel regression method to model temporal dependence via a similarity measure characterised by semi-metric, bandwidth and kernel function. Aneiros-Perez and Vieu (2008) introduced a semi-functional partial linear model that com-´ bines lin”
Nonparametric modelling for functional data: selected survey and tracks for future (2018, methodology): “the additive model [63] and sparse regression models [141,142,151] .”
Curse of dimensionality and related issues in nonparametric functional regression (2011, background): “[20, 23, 2, 22, 6, 3, 4, 7, 13] or [14] for a few paths in that direction.”