Modeling and Forecasting Daily Electricity Load Curves: A Hybrid Approach

DOI10.1080/01621459.2012.722900zbMath1379.62091arXiv1611.08632OpenAlexW2048395053MaRDI QIDQ4916922

Haeran Cho, Xavier Brossat, Yannig Goude, Qiwei Yao

Publication date: 26 April 2013

Published in: Journal of the American Statistical Association (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1611.08632

zbMATH Keywords

singular value decompositiondimension reductioncorrelation dimensiongeneralized additive modelselectricity loads

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Inference from stochastic processes and prediction (62M20) Generalized linear models (logistic models) (62J12)

Related Items

Finite sample theory for high-dimensional functional/scalar time series with applications, Short-run electricity load forecasting with combinations of stationary wavelet transforms, An autocovariance-based learning framework for high-dimensional functional time series, Clustering Nonstationary Circadian Rhythms using Locally Stationary Wavelet Representations, On projection methods for functional time series forecasting, Hierarchical Probabilistic Forecasting of Electricity Demand With Smart Meter Data, On consistency and sparsity for high-dimensional functional time series with application to autoregressions, Vector-on-function quantile regression for stationary ergodic processes

Uses Software

• gamair

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