A review of the literature on forecast reconciliation.
Review of Bayesian forecasting.
Gradient boosting on Lee Carter model with age-spatial shrinkage.
Forecast Reconciliation where a subset of forecasts are not adjusted.
Forecast combination using reference data to cross-learn weights.
Manifold Learning with Approximate Nearest Neighbors including on statistical manifolds.
The theory of probabilistic reconciliation and score optimisation by gradient descent.
Bayesian methods taking survey weights into account are proposed, evaluated and applied to estimating the Australian income distribution.
Application of hierarchical methods to Australian GDP Forecasting.
The geometric understanding of hierarchical time series and forecast reconciliation.