A framework for online forecast reconciliation is developed via multivariate linear models on graph hierarchies, ridge regression, and recursive least squares, with a demonstration on district heating load data.
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A Bayesian hierarchical model integrates coherence penalization and level-specific focus into forecasting estimation, yielding improved predictive accuracy on simulated and Australian tourism data.
Habitual lifestyle timing traits explain 42.3% of total acrophase variance in circadian heart rate rhythm while daily states explain 0.9%, based on linear mixed-effects modeling of wearable data from 105 free-living adults.
citing papers explorer
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Online forecast reconciliation using linear models
A framework for online forecast reconciliation is developed via multivariate linear models on graph hierarchies, ridge regression, and recursive least squares, with a demonstration on district heating load data.
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Hierarchical Bayes meets hierarchical forecasting: A flexible framework for level-focused forecasts
A Bayesian hierarchical model integrates coherence penalization and level-specific focus into forecasting estimation, yielding improved predictive accuracy on simulated and Australian tourism data.