simprob
attribute
to each node in the network and can be edited and used for
simulation
.makesimprob(nw,
s2=function(idx,cf) {
cf <- as.vector(cf)
xs <- (1:length(cf))
log(xs },
m0=function(idx,cf) {
cf <- as.vector(cf)
xs <- (1:length(cf))^2
.69*(xs },
m1=function(idx,cf) {
cf <- as.vector(cf)
xs <- (1:length(cf))*10
idx*(cf })
simprob
.simprob
is determined. If the node is
discrete, the probability distribution is uniform (and thus not
reflecting the dependence in the graph as it should). If the node is
continuous, one mean and variance is attached per configuration of the
discrete parents. The mean depends on the continuos parents and is the
regression coefficients determined by the functions m0
(intercept) and m1
(regression coefficients). The variance is
determined by the function s2
.simulation