Bayesian networks with likelihood evidence in R

Research output: Contribution to conference without publisher/journalConference abstract for conferenceResearchpeer-review

Abstract

The gRain package for R (www.r-project.org) has been around for a decade and the package provides tools for building Bayesian networks as well as for probability propagation in such networks.
In gRain, attention is restricted to networks with discrete nodes.
A recent addition to the package is the ability to incorporate likelihood evidence (also called soft evidence or virtual evidence) in the network. This facility is useful in itself, and the facility also allows for handling networks where not all nodes are discrete.

References
[1] Højsgaard, S. (2012). Graphical Independence Networks with the gRain Package for R. Journal
of Statistical Software 46, 1–26.
Original languageEnglish
Publication date2018
Number of pages1
Publication statusPublished - 2018
Event27th Nordic Conference in Mathematical Statistics - Dorpat Convention Centre, Tartu, Estonia
Duration: 26 Jun 201829 Aug 2018
Conference number: 27
http://nordstat2018.ut.ee/

Conference

Conference27th Nordic Conference in Mathematical Statistics
Number27
LocationDorpat Convention Centre
CountryEstonia
CityTartu
Period26/06/201829/08/2018
Internet address

Fingerprint

computer programs
propagation

Keywords

  • Message passing
  • Probability propagation

Cite this

Højsgaard, S. (2018). Bayesian networks with likelihood evidence in R. 32. Abstract from 27th Nordic Conference in Mathematical Statistics , Tartu, Estonia.
Højsgaard, Søren. / Bayesian networks with likelihood evidence in R. Abstract from 27th Nordic Conference in Mathematical Statistics , Tartu, Estonia.1 p.
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abstract = "The gRain package for R (www.r-project.org) has been around for a decade and the package provides tools for building Bayesian networks as well as for probability propagation in such networks.In gRain, attention is restricted to networks with discrete nodes.A recent addition to the package is the ability to incorporate likelihood evidence (also called soft evidence or virtual evidence) in the network. This facility is useful in itself, and the facility also allows for handling networks where not all nodes are discrete.References[1] H{\o}jsgaard, S. (2012). Graphical Independence Networks with the gRain Package for R. Journalof Statistical Software 46, 1–26.",
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author = "S{\o}ren H{\o}jsgaard",
year = "2018",
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pages = "32",
note = "27th Nordic Conference in Mathematical Statistics , NORDSTAT 2018 ; Conference date: 26-06-2018 Through 29-08-2018",
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Højsgaard, S 2018, 'Bayesian networks with likelihood evidence in R' 27th Nordic Conference in Mathematical Statistics , Tartu, Estonia, 26/06/2018 - 29/08/2018, pp. 32.

Bayesian networks with likelihood evidence in R. / Højsgaard, Søren.

2018. 32 Abstract from 27th Nordic Conference in Mathematical Statistics , Tartu, Estonia.

Research output: Contribution to conference without publisher/journalConference abstract for conferenceResearchpeer-review

TY - ABST

T1 - Bayesian networks with likelihood evidence in R

AU - Højsgaard, Søren

PY - 2018

Y1 - 2018

N2 - The gRain package for R (www.r-project.org) has been around for a decade and the package provides tools for building Bayesian networks as well as for probability propagation in such networks.In gRain, attention is restricted to networks with discrete nodes.A recent addition to the package is the ability to incorporate likelihood evidence (also called soft evidence or virtual evidence) in the network. This facility is useful in itself, and the facility also allows for handling networks where not all nodes are discrete.References[1] Højsgaard, S. (2012). Graphical Independence Networks with the gRain Package for R. Journalof Statistical Software 46, 1–26.

AB - The gRain package for R (www.r-project.org) has been around for a decade and the package provides tools for building Bayesian networks as well as for probability propagation in such networks.In gRain, attention is restricted to networks with discrete nodes.A recent addition to the package is the ability to incorporate likelihood evidence (also called soft evidence or virtual evidence) in the network. This facility is useful in itself, and the facility also allows for handling networks where not all nodes are discrete.References[1] Højsgaard, S. (2012). Graphical Independence Networks with the gRain Package for R. Journalof Statistical Software 46, 1–26.

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KW - Probability propagation

M3 - Conference abstract for conference

SP - 32

ER -

Højsgaard S. Bayesian networks with likelihood evidence in R. 2018. Abstract from 27th Nordic Conference in Mathematical Statistics , Tartu, Estonia.