Functional time series approach for forecasting very short-term electricity demand

DOI10.1080/02664763.2012.740619OpenAlexW2088281105WikidataQ58288600 ScholiaQ58288600MaRDI QIDQ5128897

Han Lin Shang

Publication date: 26 October 2020

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02664763.2012.740619

zbMATH Keywords

multivariate time seriesfunctional principal component analysisseasonal time seriesroughness penaltyordinary least-squares regressionpenalised least-squares regression

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items

Seasonal functional autoregressive models, Bootstrap in semi-functional partial linear regression under dependence, Forecasting functional time series using weighted likelihood methodology, Bayesian bandwidth estimation for a semi-functional partial linear regression model with unknown error density, On projection methods for functional time series forecasting, Dynamic structural models with covariates for short-term forecasting of time series with complex seasonal patterns

Uses Software

• Rainbow
• forecast
• fda (R)
• Forecast
• ftsa

Cites Work

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