Causally Appropriate Graphical Modelling for Time Series with Applications to Economics, Ecology and Environmental Science
Degree GrantorUniversity of Canterbury
Degree NameMaster of Science
I apply the GMTS approach to graphical modelling of time series to data sets from economics, ecology and environmental science. This approach improves on traditional approaches to modelling insofar as it selects the most parsimonius model. I improve on this approach by removing some redundancies in the GMTS approach. However, a bias in terms of which links are selected means that it is unlikely that this model will select the best causal model.