Data-based prediction and causality inference of nonlinear dynamics
From MaRDI portal
Publication:1741984
DOI10.1007/s11425-017-9177-0zbMath1383.92012arXiv1710.11318OpenAlexW2964272794MaRDI QIDQ1741984
Siyang Leng, Luo-Nan Chen, Huan-Fei Ma
Publication date: 11 April 2018
Published in: Science China. Mathematics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1710.11318
Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to biology and medical sciences; meta analysis (62P10) General biostatistics (92B15)
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Detecting Causality in Complex Ecosystems
- Data based identification and prediction of nonlinear and complex dynamical systems
- Measuring the strangeness of strange attractors
- Nonlinear prediction of chaotic time series
- State space reconstruction in the presence of noise
- Embedology
- Nonlinear state estimation, indistinguishable states, and the extended Kalman filter
- Evaluating causal relations in neural systems: Granger causality, directed transfer function and statistical assessment of significance
- Nonlinear analyses of interictal EEG map the brain interdependences in human focal epilepsy.
- Effective scaling regime for computing the correlation dimension from chaotic time series
- Differentiable manifolds
- Practical implementation of nonlinear time series methods: The <scp>TISEAN</scp> package
- Modeling Biological Systems
- Independent coordinates for strange attractors from mutual information
- A unified approach to attractor reconstruction
- NONLINEAR FORECASTING OF SPIKE TRAINS FROM SENSORY NEURONS
- NONLINEAR TIME SEQUENCE ANALYSIS
- Takens embedding theorems for forced and stochastic systems
- Regularity of embeddings of infinite-dimensional fractal sets into finite-dimensional spaces
- Nonlinear Time Series Analysis
- Investigating Causal Relations by Econometric Models and Cross-spectral Methods
- Exploring complex networks
- A Statistical Framework to Infer Delay and Direction of Information Flow from Measurements of Complex Systems
- Stable signal recovery from incomplete and inaccurate measurements
- Predicting Time Series from Short-Term High-Dimensional Data
- Nonlinear forecasting for the classification of natural time series
- A robust method for detecting interdependences: Application to intracranially recorded EEG
