Assessing Nonlinear Granger Causality from Multivariate Time Series

By Xiaohai Sun. 2008

35 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Economics and Econometrics, Statistical and Nonlinear Physics

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Leila Wehbe
2. Aaditya Ramdas
3. E.J. Candes
4. Leying Guan

In Economics and Econometrics

1. Leila Wehbe
2. Aaditya Ramdas

In Statistical and Nonlinear Physics

1. Leila Wehbe
2. Aaditya Ramdas

Citations in the corpus

• Nonparametric Independence Testing for Small Sample Sizes (2014, methodology): “spensable part of machine learning. The long list of applications includes kernel PCA [1], dimension reduction [2], structure discovery [3], independence testing [4], Granger causality in time series [5], learning graphical models [6], feature learning [7], target or conditional shift [8] and kernel”
• Causality Between Energy and Output in the Long-Run (2013, unknown): “Another kernel-based approach is developed by Sun (2008).”