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9781627059787: Exploratory Causal Analysis With Time Series Data

Synopsis

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

A practicing analyst can explore the literature to find many proposals for identifying drivers and causal connections in time series data sets. Exploratory causal analysis (ECA) provides a framework for exploring potential causal structures in time series data sets and is characterized by a myopic goal to determine which data series from a given set of series might be seen as the primary driver. In this work, ECA is used on several synthetic and empirical data sets, and it is found that all of the tested time series causality tools agree with each other (and intuitive notions of causality) for many simple systems but can provide conflicting causal inferences for more complicated systems. It is proposed that such disagreements between different time series causality tools during ECA might provide deeper insight into the data than could be found otherwise.

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À propos de l?auteur

James M. McCracken, George Mason University, USA.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

  • ÉditeurMorgan and Claypool Life Sciences
  • Date d'édition2016
  • ISBN 10 1627059784
  • ISBN 13 9781627059787
  • ReliureBroché
  • Langueanglais
  • Nombre de pages147
  • Coordonnées du fabricantnon disponible

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9783031007811: Exploratory Causal Analysis with Time Series Data

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ISBN 10 :  3031007816 ISBN 13 :  9783031007811
Editeur : Springer, 2016
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James M. McCracken (author)
Edité par Morgan & Claypool Publishers, 2016
ISBN 10 : 1627059784 ISBN 13 : 9781627059787
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Soft cover. Etat : As New. This book has been in storage since publication and is unread. Hence the description as new . N° de réf. du vendeur 2305332

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