Handbook of time series analysis: recent theoretical developments and applications

Björn Schelter, Matthias Winterhalder, Jens Timmer9783527406234, 3527406239

This handbook provides an up-to-date survey of current research topics and applications of time series analysis methods written by leading experts in their fields. It covers recent developments in univariate as well as bivariate and multivariate time series analysis techniques ranging from physics’ to life sciences’ applications. Each chapter comprises both methodological aspects and applications to real world complex systems, such as the human brain or Earth’s climate. Covering an exceptionally broad spectrum of topics, beginners, experts and practitioners who seek to understand the latest developments will profit from this handbook.

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Table of contents :
Frontmatter.pdf……Page 1
Contents……Page 5
CH01 Handbook of Time Series Analysis – Introduction and Overview.pdf……Page 19
CH02 Nonlinear Analysis of Time Series Data.pdf……Page 23
CH03 Local and Cluster Weighted Modeling for Time Series Prediction.pdf……Page 56
CH04 Deterministic and Probabilistic Forecasting in Reconstructed State Spaces.pdf……Page 83
CH05 Dealing with Randomness in Biosignals.pdf……Page 105
CH06 Robust Detail-Preserving Signal Extraction.pdf……Page 147
CH07 Coupled Oscillators Approach in Analysis of Bivariate Data.pdf……Page 174
CH08 Nonlinear Dynamical Models from Chaotic Time Series – Methods and Applications.pdf……Page 196
CH09 Data-Driven Analysis of Nonstationary Brain Signals.pdf……Page 227
CH10 Synchronization Analysis and Recurrence in Complex Systems.pdf……Page 245
CH11 Detecting Coupling in the Presence of Noise and Nonlinearity.pdf……Page 279
CH12 Linear Models for Mutivariate Time Series.pdf……Page 297
CH13 Spatio-Temporal Modeling for Biosurveillance.pdf……Page 323
CH14 Graphical Modeling of Dynamic Relationships in Multivariate Time Series.pdf……Page 349
CH15 Multivariate Signal Analysis by Parametric Models.pdf……Page 387
CH16 Computer Intensive Testing for the Influence Between Time Series.pdf……Page 424
CH17 Granger Causality Basic Theory and Application to Neuroscience.pdf……Page 450
CH18 Granger Causality on Spatial Manifolds – Applications to Neuroimaging.pdf……Page 474
Index.pdf……Page 505