A SARIMAX coupled modelling applied to individual load curves intraday forecasting

DOI10.1080/02664763.2013.785496OpenAlexW2073471197MaRDI QIDQ5129024

Frédéric Proïa, Sophie Bercu

Publication date: 26 October 2020

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

Full work available at URL: https://arxiv.org/abs/1207.0360

zbMATH Keywords

seasonalitystationaritytime series analysisforecastingexogenous covariatesindividual load curveSARIMA(X) modelling

Mathematics Subject Classification ID

Statistics (62-XX)

Uses Software

• AS 182
• itsmr
• AS 154

Cites Work

• Testing the null hypothesis of stationarity against the alternative of a unit root. How sure are we that economic time series have a unit root?
• Bandwidth selection for functional time series prediction
• Time series: theory and methods.
• Triple seasonal methods for short-term electricity demand forecasting
• Robust forecasting with exponential and Holt-Winters smoothing
• A Functional Wavelet–Kernel Approach for Time Series Prediction
• Testing for unit roots in autoregressive-moving average models of unknown order
• Algorithm AS 154: An Algorithm for Exact Maximum Likelihood Estimation of Autoregressive-Moving Average Models by Means of Kalman Filtering
• On a measure of lack of fit in time series models
• Periodic Seasonal Reg-ARFIMA–GARCH Models for Daily Electricity Spot Prices
• Distribution of Residual Autocorrelations in Autoregressive-Integrated Moving Average Time Series Models
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