Elements of Nonlinear Time Series Analysis and Forecasting
This book provides an overview of the current state-of-the-art of nonlinear time series analysis, richly illustrated with examples, pseudocode algorithms and real-world applications. Avoiding a “theorem-proof” format, it shows concrete applications on a variety of empirical time series. The book can...
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| Language: | English |
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Cham :
Springer International Publishing : Imprint: Springer,
2017.
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| Edition: | 1st ed. 2017. |
| Series: | Springer Series in Statistics,
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| Online Access: | https://doi.org/10.1007/978-3-319-43252-6 |
Table of Contents:
- Introduction and Some Basic Concepts
- Classic Nonlinear Models
- Probabilistic Properties
- Frequency-Domain Tests
- Time-Domain Linearity Tests
- Model Estimation, Selection and Checking
- Tests for Serial Independence
- Time-Reversibility
- Semi- and Nonparametric Forecasting
- Forecasting Vector Parametric Models and Methods
- Vector Semi- and Nonparametric Methods. .