he topics of interest include, but are not limited to:
1.- Time Series Analysis and Forecasting:
- Nonparametric and functional methods
- Vector processes
- Probabilistic approaches to modeling macroeconomic uncertainties
- Uncertainties in forecasting processes
- Nonstationarity
- Forecasting with Many Models. Model integration
- Forecasting theory and adjustment
- Ensemble forecasting
- Forecasting performance evaluation
- Interval forecasting
- Econometric models
- Econometric Forecasting
- Data preprocessing methods: Data decomposition, seasonal adjustment, singular spectrum analysis, detrending methods, etc.
2.- Advanced methods and on-line learning in time series:
- Adaptivity for stochastic models
- On-line machine learning for forecasting
- Aggregation of predictors
- Hierarchical forecasting
- Forecasting with computational intelligence
- Time series analysis with computational intelligence
- Integration of system dynamics and forecasting models
3.- High Dimensional and Complex/Big Data
- Local vs global forecasts
- Dimension reduction techniques
- Multiscaling
- Forecasting Complex/Big data
4.- Forecasting in real problems:
- Health forecasting
- Telecommunication forecasting
- Modelling and forecasting in power markets
- Energy forecasting
- Financial forecasting and risk analysis
- Forecasting electricity load and prices
- Forecasting and planning systems
- Real time macroeconomic monitoring and forecasting
- Applications in: energy, finance, transportation, networks, meteorology, health, research and environment, etc.
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