Granger causality using Jacobian in neural networks

Granger causality is a commonly used method for uncovering information flow and dependencies in a time series. Here, we introduce JGC (Jacobian Granger causality), a neural network-based approach to Granger causality using the Jacobian as a measure of variable importance, and propose a variable sele...

Full description

Saved in:
Bibliographic Details
Main Authors: Suryadi, Chew, Lock Yue, Ong, Yew Soon
Other Authors: School of Physical and Mathematical Sciences
Format: Article
Language:English
Published: 2023
Subjects:
Online Access:https://hdl.handle.net/10356/165593
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Nanyang Technological University
Language: English

Similar Items