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Beskrivning
However, a modeling framework incorporating stochastic models, likelihood calculation, prediction intervals and procedures for model selection, was not developed until recently. More advanced topics are covered in Part 3, including the mathematical properties of the models and extensions of the models for specific problems.
Basic Concepts.- Getting Started.- Essentials.- Linear Innovations State Space Models.- Nonlinear and Heteroscedastic Innovations State Space Models.- Estimation of Innovations State Space Models.- Prediction Distributions and Intervals.- Selection of Models.- Further Topics.- Normalizing Seasonal Components.- Models with Regressor Variables.- Some Properties of Linear Models.- Reduced Forms and Relationships with ARIMA Models.- Linear Innovations State Space Models with Random Seed States.- Conventional State Space Models.- Time Series with Multiple Seasonal Patterns.- Nonlinear Models for Positive Data.- Models for Count Data.- Vector Exponential Smoothing.- Applications.- Inventory Control Applications.- Conditional Heteroscedasticity and Applications in Finance.- Economic Applications: The Beveridge–Nelson Decomposition.