Optimal combination forecasts for hierarchical time series

DOI10.1016/j.csda.2011.03.006zbMath1464.62095OpenAlexW2073210389WikidataQ58288617 ScholiaQ58288617MaRDI QIDQ125611

Han Lin Shang, Roman A. Ahmed, George Athanasopoulos, Rob Hyndman, Roman A. Ahmed, Rob Hyndman, George Athanasopoulos, Han Lin Shang

Publication date: September 2011

Published in: Computational Statistics & Data Analysis, Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/1885/196566

zbMATH Keywords

combining forecastshierarchical forecastingbottom-up forecastingGLS regressionreconciling forecaststop-down forecasting

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Inference from stochastic processes and prediction (62M20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10)

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Uses Software

• LSQR
• forecast
• Forecast
• SparseM
• CRAIG

Cites Work

• Unnamed Item
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• When is an aggregate of a time series efficiently forecast by its past?
• An investigation of aggregate variable time series forecast strategies with specific subaggregate time series statistical correlation
• On equality and proportionality of ordinary least squares, weighted least squares and best linear unbiased estimators in the general linear model
• Aggregation and Proration in Forecasting
• Block Sparse Cholesky Algorithms on Advanced Uniprocessor Computers
• An overview of the sparse basic linear algebra subprograms
• Calculating the Singular Values and Pseudo-Inverse of a Matrix