Exploratory Causal Analysis in Bivariate Time Series Data

Many scientific disciplines rely on observational data of systems for which it is difficult (or impossible) to implement controlled experiments and data analysis techniques are required for identifying causal information and relationships directly from observational data. This need has lead to the development of many different time series causality approaches and tools including transfer entropy, convergent cross-mapping (CCM), and Granger causality statistics.

Author

• McCracken, James M.

• Physics
• Causality
• Granger
• Leaning
• Pairwise asymmetric inference
• Penchant
• Time series analysis

Identifier

hdl:1920/10169

OAI identifier oai:identifier

oai:MARS:1920/10169