gistfile1.r

#install.packages("catnet",71)
library(catnet)

## Build network
cnet <- cnNew(nodes = c("S", "L", "F", "T", "C"), cats = list(c("winter", "spring", "summer","fall"), 
c("NA","SA"), c("salmon","bass"), c("wide","thin"), c("light","medium","dark")), 
parents = list(NULL, NULL, c(1,2),c(3),c(3)), probs = 
  list(
    c(.1,.2,.5,.2), 
    c(0.6, 0.4), 
    list(list(c(0.5,0.5),c(0.7,0.3)),list(c(0.6,0.4),c(0.8,0.2)),list(c(0.4,0.6),c(0.1,0.9)),list(c(0.2,0.8),c(0.3,0.7))),
    list(c(0.3,0.7),c(0.6,0.4)),
    list(c(0.6,0.2,0.2),c(0.2,0.3,0.5))
  )
)

## Distributions 
cnProb(cnet)

## Marginal Distribution for type of fish 
cnNodeMarginalProb(cnet, node=3)

## Marginal Distribution for thickness
cnNodeMarginalProb(cnet, node=4)


## 
cnNodeMarginalProb(cnet, node=5)


## Posterior probability distribution of the season given L=NA and C=dark? 
cnCondProb(cnet, x=c("S"="winter"), y=c("L"="NA","C"="dark"))
cnCondProb(cnet, x=c("S"="spring"), y=c("L"="NA","C"="dark"))
cnCondProb(cnet, x=c("S"="summer"), y=c("L"="NA","C"="dark"))
cnCondProb(cnet, x=c("S"="fall"), y=c("L"="NA","C"="dark"))


cnCondProb(cnet, x=c("S"="winter"), y=c("C"="dark"))
cnCondProb(cnet, x=c("S"="spring"), y=c("C"="dark"))
cnCondProb(cnet, x=c("S"="summer"), y=c("C"="dark"))
cnCondProb(cnet, x=c("S"="fall"), y=c("C"="dark"))