Memory Matters: A Case for Granger Causality in Climate Variability Studies

By Marie C. McGraw, Elizabeth A. Barnes. 2018

114 citations recorded by the source corpus.

Subfields: Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/ad07ea5a4a18e924f7a504350cf85eb2b3e031dc

How researchers see this paper

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

In Global and Planetary Change

1. Anuj Karpatne
2. Vipin Kumar
3. S. Ravela

Citations in the corpus

• Machine Learning for the Geosciences: Challenges and Opportunities (2017, methodology): “As for causality analysis, the most common tool used to date in the geosciences is bivariate Granger analysis [83], followed by multi-variate Granger analysis using vector”