gmvalid-package {gmvalid}R Documentation

Validation of graphical models

Description

This package provides functions among others that can be used to analyse graphical models. This includes e.g. the possibility to simulate data sets given a dependence model, to analyze discrete graphical models utilizing the MIM program or the CoCo package and to quantify associations or interactions.

Furthermore, the uncertainty of a selected graphical model can be described using the bootstrap or the best prediction model can be evaluated for a dichotomous outcome variable and several discrete influences using cross validation.

Details

Package: gmvalid
Type: Package
Version: 1.21
Date: 2009-11-01
License: GPL (>=2)

Note

This work has been supported by the German Research Foundation
(DFG: http://www.dfg.de) under grant scheme PI 345/2-1.

Author(s)

Ronja Foraita, Fabian Sobotka
Bremen Institute for Prevention Research and Social Medicine
(BIPS) http://www.bips.uni-bremen.de

References

> MIM (http://www.hypergraph.dk/)
Edwards D (2002) An Introduction to Graphical Modelling. Springer

> mimR (http://genetics.agrsci.dk/~sorenh/mimR/index.html)
Højsgaard S (2004) The mimR package for graphical modelling in R. Journal of Statistical Software, 11(6).

> CoCo (http://www.badsberg.eu)
Badsberg JH (2001) A guide to CoCo. Journal of Statistical Software, 6(4).

> CSI
Foraita R (2008) A conditional synergy index to assess biological interaction. http://nbn-resolving.de/urn:nbn:de:gbv:46-diss000111139

See Also

mimR, CoCo

Examples

    ### Generates a data frame given a dependence model
    gm.a <- gm.modelsim(1000,"ABC,CDE")
    
    ### Modelselection with graphical output
    gm.analysis(gm.a)   
    
    ### Model validation using the bootstrap 
    gm.boot.coco(100,gm.a,recursive=TRUE,follow=TRUE)

    ### Model prediction using cross validation
    ### Example works!
    ## Not run: gm.cv(3,data=gm.a,strategy="f",options="b")
    
    ### Testing interaction on the penetrance scale
    ### using the conditional synergy index (CSI)
    gm.csi(1,2,3,data=gm.a)

    ### Testing interaction on a additivity scale
    ### using the synergy index (S)
    gm.si(1,2,3,data=gm.a)   

    ### Gamma Coefficient B indpendent D given C
    gm.gamma(2,4,data=gm.a,conditions=3)


[Package gmvalid version 1.21 Index]