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The Frugal Inference of Causal Relations

Datos Bibliográficos

ID8399210
AutoresMalcolm Forster (University of Wisconsin–Madison, autor de correspondencia), Garvesh Raskutti (0000-0002-0522-5423, University of Wisconsin–Madison, autor de correspondencia), Richard Stern (0000-0003-0034-1385, Munich School of Philosophy, autor de correspondencia), Reuben Stern, Nanci Weinberger (0000-0002-4011-5756, Tilburg University, autor de correspondencia), Naftali Weinberger
Año2018
Volumen69
Número3
Páginas821-848
Fecha de publicación2018-09-01
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaThe British Journal for the Philosophy of Science (JOURNAL)
Identificadores de la revistaISSN: 0007-0882 • E-ISSN: 1464-3537
EditorialOxford University Press (PUBLISHER • GB)
DOI10.1093/bjps/axw033
OpenAlexW2761717464
IdiomaEN
Citas recibidas6
Referencias citadas16

Recent approaches to causal modelling rely upon the causal Markov condition, which specifies which probability distributions are compatible with a directed acyclic graph (DAG). Further principles are required in order to choose among the large number of DAGs compatible with a given probability distribution. Here we present a principle that we call frugality. This principle tells one to choose the DAG with the fewest causal arrows. We argue that frugality has several desirable properties compared to the other principles that have been suggested, including the well-known causal faithfulness condition. 1 Introduction2 The Causal Markov Condition3 Faithfulness4 Frugality 4.1 Basic independences and frugality 4.2 General properties of directed acyclic graphs satisfying frugality 4.3 Connection to minimality assumptions5 Frugality as a Parsimony Principle6 Conclusion Appendix

Algorithm · Causal inference · Causality (physics) · Directed acyclic graph · Econometrics · Frugality · Machine learning · Markov chain · Mathematical economics · Bayesian Modeling and Causal Inference · Computer Science · Law · Mathematics · Philosophy and History of Science · Theoretical Computer Science

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Obras citantes distintas6
Citas por año0,86
Intervalo de citas2019 - 2025 (7)
Velocidad de citaciónrecent
Altamente citadoNo
Tipos de citaNeutras: 4
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