- Statistical methodology:
- General statistics
- Time series analysis
- Forecasting
- Multivariate statistics
- Stochastic simulation
- Data mining
- Bayesian statistics
- Combining computer models and stochastic models
- Complex modelling
- Regression, including
- shrinkage regression (PLS, ridge, Lasso, reduced rank etc.)
- nonlinear regression (GAM, neural networks, projection pursuit, MARS, AVAS etc.)
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- Applications within forecasting and time series:
- Weather
- Teletraffic volume
- Tax income
- Water flow
- Electricity demand
- Electricity price
- Metal price
- Oil demand
- Grain price
- Newspaper sales
- Bacterial resistance to antibiotics
- Predicting biomass in fish farming
- Predicting blood donor arrival
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- Other applications:
- Paper production
- Newspaper printing
- Traffic counting
- Whale catching management
- Estimating catch-at-age of cod
- Empirical models for air pollution, traffic and meteorology
- Water pollution
- Health effects of air pollution
- Clinical trials
- Modeling of a smelting furnace
- Train networks
- Predicting soccer World Cup
- Surveys by web
- Insurance
- Credit scoring
- Software engineering
- Bioinformatics
- Estimation of copyright volume
- Spread of infectious diseases in fish farming
- Climate change
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