Abstract
I: Introduction to State Space Modeling.- 1. The SSATS algorithm and subspace methods.- 2. A guide to state space modeling of multiple time series.- II: Applications of State Space Algorithm.- 1. Evaluating state space forecasts of soybean complex prices.- 2. A state space model of monthly US wheat prices.- 3. Managing the heard: price forecasts for California cattle production.- 4. Labor market and cyclical fluctuations.- 5. Modeling cointegrated processes by a vector-valued state space algorithm.- 6. A method for identification of combined deterministic stochastic systems.- 7. Competing exchange rate models.- 8. Application of state-space models to ocean climate varibility in the northeast pacific ocean.- III: Applications of Neural Networks.- 1. On the equivalence between ARMA models and simple recurrent neural networks.- 2. Forecasting stock market indicies with recurrent neural networks.
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