Detecting Causality from Nonlinear Dynamics with Short-term Time Series
نویسندگان
چکیده
منابع مشابه
Detecting Causality from Nonlinear Dynamics with Short-term Time Series
Quantifying causality between variables from observed time series data is of great importance in various disciplines but also a challenging task, especially when the observed data are short. Unlike the conventional methods, we find it possible to detect causality only with very short time series data, based on embedding theory of an attractor for nonlinear dynamics. Specifically, we first show ...
متن کاملDetecting Nonlinear Causality in Multivariate Time Series with Sparse Additive Models
We propose a nonparametric method for detecting nonlinear causal relationship within a set of multidimensional discrete time series, by using sparse additive models (SpAMs). We show that, when the input to the SpAM is a β-mixing time series, the model can be fitted by first approximating each unknown function with a linear combination of a set of B-spline bases, and then solving a group-lasso-t...
متن کاملAnalyzing Multiple Nonlinear Time Series with Extended Granger Causality
Identifying causal relations among simultaneously acquired signals is an important problem in multivariate time series analysis. For linear stochastic systems Granger proposed a simple procedure called the Granger causality to detect such relations. In this work we consider nonlinear extensions of Granger’s idea and refer to the result as Extended Granger Causality. A simple approach implementi...
متن کاملThe Coupling Spectrum: a New Method for Detecting Temporal Nonlinear Causality in Financial Time Series
Identifying dynamic causal relationships between financial time series may help explain market dynamics. The Granger causality (G-causality) test is a method to detect linear causal relationships between time series. However, there exists significant evidence for nonlinear causality between financial time series. Hence, several nonlinear extensions of G-causality (NLG-causality) were proposed. ...
متن کاملDetecting Nonlinear Causality via Nonlinear Modeling
We analyze a set of complex time series from the view point of nonlinear causality. The mathematical background for analyzing time series is an extension of embedding theories of autonomous systems to an input{output system. We consider that the existence of nonlinear causality can be detected by nonlinear predictability of input and output sequences. Several numerical examples are given for co...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Scientific Reports
سال: 2014
ISSN: 2045-2322
DOI: 10.1038/srep07464