Modeling and Stochastic Learning for Forecasting in High Dimensions
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- Artikel-Nr.: 10441633
Beschreibung
1 Short Term Load Forecasting in the Industry for Establishing Consumption Baselines: A French Case.- 2 Confidence intervals and tests for high-dimensional models: a compact review.- 3 Modelling and forecasting daily electricity load via curve linear regression.- 4 Constructing Graphical Models via the Focused Information Criterion.- 5 Nonparametric short term Forecasting electricity consumption with IBR.- 6 Forecasting the electricity consumption by aggregating experts.- 7 Flexible and dynamic modeling of dependencies via copulas.- 8 Operational and online residential baseline estimation.- 9 Forecasting intra day load curves using sparse functional regression.- 10 Modelling and Prediction of Time Series Arising on a Graph.- 11 GAM model based large scale electrical load simulation for smart grids.- 12 Spot volatility estimation for high-frequency data: adaptive estimation in practice.- 13 Time series prediction via aggregation: an oracle bound including numerical cost.- 14 Space-time trajectories of wind power generation: Parametrized precision matrices under a Gaussian copula approach.- 15 Game-theoretically Optimal Reconciliation of Contemporaneous Hierarchical Time Series Forecasts.- 16 The BAGIDIS distance: about a fractal topology, with applications to functional classification and prediction.
Eigenschaften
Breite: | 158 |
Höhe: | 235 |
Länge: | 20 |
Seiten: | 339 |
Sprachen: | Englisch |
Autor: | Anestis Antoniadis, Jean-Michel Poggi, Xavier Brossat |
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