getarcs {rWMBAT}R Documentation

Builds The Adjacency Matrix For A Set Of Variables

Description

By comparing mutual information between two variables to thresholds determined seperately, this function declares there to be an arc in a Bayesian network. Arcs are stored in an adjacency matrix, described below.

Usage

getarcs(mvc, vcthreshold, mvv, vvthreshold)

Arguments

mvc double vector array with mutual information between variables and the class (variables and other variables). The (i,j) entries of mvv are MI(Vi,Vj)
vcthreshold scalar threshold used to test for existence linkz
mvv double vector matrix
vvthreshold scalar threshold used to test for existence linkz

Details

The primary tests are MI[Vi,Cj]>>vcthreshold (tests for links between Vi and the class) MI[Vi,Vj]>>vvthreshold (tests the links between variables)

Value

logical matrix whose entries "1" at (i,j) mean "an arc exists from the Bayesian network node Vi to Vj." The class variable C is added at row (number of V's + 1). "0" values mean no arc

Author(s)

Karl Kuschner, Qian Si and William Cooke, College of William and Mary, Dept. of Physics, 2009

References

http://kwkusc.people.wm.edu/dissertation/dissertation.htm

Examples

data(mi_vc, vcthreshold, mi_vv, vvthreshold) # load the example input data from the package
adjmat<-getarcs(mi_vc, vcthreshold, mi_vv, vvthreshold)
         

[Package rWMBAT version 2.0 Index]