Causally Appropriate Graphical Modelling for Time Series with Applications to Economics, Ecology and Environmental Science

Causally Appropriate Graphical Modelling for Time Series with Applications to Economics, Ecology and Environmental 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...

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Bibliographic Details
Main Author: Meurk, Carla Siobhan
Language:en
Published: University of Canterbury. Mathematics and Statistics 2008
Subjects:
Graphical Modelling
Causality
Time Series
Online Access:http://hdl.handle.net/10092/1152
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spelling ndltd-canterbury.ac.nz-oai-ir.canterbury.ac.nz-10092-11522015-03-30T15:28:52ZCausally Appropriate Graphical Modelling for Time Series with Applications to Economics, Ecology and Environmental ScienceMeurk, Carla SiobhanGraphical ModellingCausalityTime SeriesI 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.University of Canterbury. Mathematics and Statistics2008-09-07T22:36:15Z2008-09-07T22:36:15Z2005Electronic thesis or dissertationTexthttp://hdl.handle.net/10092/1152enNZCUCopyright Carla Siobhan Meurkhttp://library.canterbury.ac.nz/thesis/etheses_copyright.shtml
collection NDLTD
language en
sources NDLTD
topic Graphical Modelling
Causality
Time Series
spellingShingle Graphical Modelling
Causality
Time Series
Meurk, Carla Siobhan
Causally Appropriate Graphical Modelling for Time Series with Applications to Economics, Ecology and Environmental Science
description 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.
author Meurk, Carla Siobhan
author_facet Meurk, Carla Siobhan
author_sort Meurk, Carla Siobhan
title Causally Appropriate Graphical Modelling for Time Series with Applications to Economics, Ecology and Environmental Science
title_short Causally Appropriate Graphical Modelling for Time Series with Applications to Economics, Ecology and Environmental Science
title_full Causally Appropriate Graphical Modelling for Time Series with Applications to Economics, Ecology and Environmental Science
title_fullStr Causally Appropriate Graphical Modelling for Time Series with Applications to Economics, Ecology and Environmental Science
title_full_unstemmed Causally Appropriate Graphical Modelling for Time Series with Applications to Economics, Ecology and Environmental Science
title_sort causally appropriate graphical modelling for time series with applications to economics, ecology and environmental science
publisher University of Canterbury. Mathematics and Statistics
publishDate 2008
url http://hdl.handle.net/10092/1152
work_keys_str_mv AT meurkcarlasiobhan causallyappropriategraphicalmodellingfortimeserieswithapplicationstoeconomicsecologyandenvironmentalscience
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