Graphical modelling software in R - status

Claus Dethlefsen, Søren Højsgaard, Steffen L. Lauritzen

Research output: Contribution to conference without publisher/journalPosterResearch

Abstract

Graphical models in their modern form have been around for nearly a quarter of a century.  Various computer programs for inference in graphical models have been developed over that period. Some examples of free software programs are BUGS (Thomas 1994), CoCo (Badsberg2001), Digram (Klein, Keiding, and Kreiner 1995), MIM (Edwards  2000), and Tetrad (Glymour, Scheines, Spirtes, and Kelley 1987). The gR initiative (Lauritzen 2002) aims at making graphical models available in R (R Development Core Team 2006). A small grant from the Danish Science Foundation supported this initiative. We will summarize the results of the initiative so far. Specifically we will illustrate some of the R packages for graphical modelling currently on CRAN and discuss their strengths and weaknesses.
Original languageEnglish
Publication date2007
Number of pages1
Publication statusPublished - 2007
EventDirections in Statistical Computing - Auckland, New Zealand
Duration: 15 Feb 200716 Feb 2007

Conference

ConferenceDirections in Statistical Computing
CountryNew Zealand
CityAuckland
Period15/02/200716/02/2007

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Graphical Modeling
Graphical Models
Software

Cite this

Dethlefsen, C., Højsgaard, S., & Lauritzen, S. L. (2007). Graphical modelling software in R - status. Poster session presented at Directions in Statistical Computing, Auckland, New Zealand.
Dethlefsen, Claus ; Højsgaard, Søren ; Lauritzen, Steffen L. / Graphical modelling software in R - status. Poster session presented at Directions in Statistical Computing, Auckland, New Zealand.1 p.
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Dethlefsen, C, Højsgaard, S & Lauritzen, SL 2007, 'Graphical modelling software in R - status', Auckland, New Zealand, 15/02/2007 - 16/02/2007, .

Graphical modelling software in R - status. / Dethlefsen, Claus; Højsgaard, Søren; Lauritzen, Steffen L.

2007. Poster session presented at Directions in Statistical Computing, Auckland, New Zealand.

Research output: Contribution to conference without publisher/journalPosterResearch

TY - CONF

T1 - Graphical modelling software in R - status

AU - Dethlefsen, Claus

AU - Højsgaard, Søren

AU - Lauritzen, Steffen L.

N1 - Titel på proceedings: DSC Proceedings

PY - 2007

Y1 - 2007

N2 - Graphical models in their modern form have been around for nearly a quarter of a century.  Various computer programs for inference in graphical models have been developed over that period. Some examples of free software programs are BUGS (Thomas 1994), CoCo (Badsberg2001), Digram (Klein, Keiding, and Kreiner 1995), MIM (Edwards  2000), and Tetrad (Glymour, Scheines, Spirtes, and Kelley 1987). The gR initiative (Lauritzen 2002) aims at making graphical models available in R (R Development Core Team 2006). A small grant from the Danish Science Foundation supported this initiative. We will summarize the results of the initiative so far. Specifically we will illustrate some of the R packages for graphical modelling currently on CRAN and discuss their strengths and weaknesses.

AB - Graphical models in their modern form have been around for nearly a quarter of a century.  Various computer programs for inference in graphical models have been developed over that period. Some examples of free software programs are BUGS (Thomas 1994), CoCo (Badsberg2001), Digram (Klein, Keiding, and Kreiner 1995), MIM (Edwards  2000), and Tetrad (Glymour, Scheines, Spirtes, and Kelley 1987). The gR initiative (Lauritzen 2002) aims at making graphical models available in R (R Development Core Team 2006). A small grant from the Danish Science Foundation supported this initiative. We will summarize the results of the initiative so far. Specifically we will illustrate some of the R packages for graphical modelling currently on CRAN and discuss their strengths and weaknesses.

M3 - Poster

ER -

Dethlefsen C, Højsgaard S, Lauritzen SL. Graphical modelling software in R - status. 2007. Poster session presented at Directions in Statistical Computing, Auckland, New Zealand.