University of Jyväskylä | JYX Digital Repository

  • English  | Give feedback |
    • suomi
    • English
 
  • Login
JavaScript is disabled for your browser. Some features of this site may not work without it.
View Item 
  • JYX
  • Artikkelit
  • Matemaattis-luonnontieteellinen tiedekunta
  • View Item
JYX > Artikkelit > Matemaattis-luonnontieteellinen tiedekunta > View Item

Enhancing Identification of Causal Effects by Pruning

ThumbnailPublisher's PDF
View/Open
464.6Kb

Downloads:  
Show download detailsHide download details  
Tikka, S., & Karvanen, J. (2018). Enhancing Identification of Causal Effects by Pruning. Journal of Machine Learning Research, 18, 1-23. Retrieved from http://www.jmlr.org/papers/volume18/17-563/17-563.pdf
Published in
Journal of Machine Learning Research
Authors
Tikka, Santtu |
Karvanen, Juha
Date
2018
Discipline
Tilastotiede
Copyright
© the Authors, 2018.

 
Causal models communicate our assumptions about causes and effects in real-world phenomena. Often the interest lies in the identification of the effect of an action which means deriving an expression from the observed probability distribution for the interventional distribution resulting from the action. In many cases an identifiability algorithm may return a complicated expression that contains variables that are in fact unnecessary. In practice this can lead to additional computational burden and increased bias or inefficiency of estimates when dealing with measurement error or missing data. We present graphical criteria to detect variables which are redundant in identifying causal effects. We also provide an improved version of a well-known identifiability algorithm that implements these criteria.
Publisher
MIT Press
ISSN Search the Publication Forum
1532-4435
Keywords
kausaliteetti tunnistaminen algoritmit causal inference identiafiability causal model pruning algorithm

Original source
http://www.jmlr.org/papers/volume18/17-563/17-563.pdf

URI

http://urn.fi/URN:NBN:fi:jyu-201807043469

Metadata
Show full item record
Collections
  • Matemaattis-luonnontieteellinen tiedekunta [3586]
  • Browse materials
  • Browse materials
  • Articles
  • Conferences and seminars
  • Electronic books
  • Historical maps
  • Journals
  • Tunes and musical notes
  • Photographs
  • Presentations and posters
  • Publication series
  • Research reports
  • Research data
  • Study materials
  • Theses

Browse

All of JYXCollection listBy Issue DateAuthorsSubjectsPublished inDepartmentDiscipline

My Account

Login

Statistics

View Usage Statistics
  • How to publish in JYX?
  • Self-archiving
  • Publish Your Thesis Online
  • Publishing Your Dissertation
  • Publication services

Open Science at the JYU
 
Data Protection Description

Accessibility Statement
Open Science Centre