# Initalize an mrf-object:
library(CRFutil)
library(Rgraphviz)
# Check and see if Pr(X) ~= prod Pr(Xi|X/Xi)
# Graph formula: Schmidt Chain
grphf <- ~A:B + B:C + C:D
# Check the graph:
gp <- ug(grphf, result = "graph")
dev.off()
plot(gp)
dev.off()
iplot(gp)
adj <- ug(grphf, result="matrix")
adj
n.states <- 2
mc <- make.crf(adj, n.states)
# These are what CRF takes as inputs/fits. The "potentials".
Psi1 <- c(0.25, 0.75)*4
Psi2 <- c(0.9, 0.1) *10
Psi3 <- c(0.25, 0.75)*4
Psi4 <- c(0.9, 0.1) *10
Psi12 <-
6*rbind(c(2/6, 1/6),
c(1/6, 2/6))
Psi23 <-
6*rbind(c(2/6, 1/6),
c(1/6, 2/6))
Psi34 <-
6*rbind(c(2/6, 1/6),
c(1/6, 2/6))
mc$node.pot[1,] <- Psi1
mc$node.pot[2,] <- Psi2
mc$node.pot[3,] <- Psi3
mc$node.pot[4,] <- Psi4
mc$edges # Check!
mc$edge.pot[[1]] <- Psi12
mc$edge.pot[[2]] <- Psi23
mc$edge.pot[[3]] <- Psi34
# Check again!
mc$node.pot
mc$edge.pot
s1<-1
s2<-2
st.sp <- expand.grid(c(s1,s2),c(s1,s2),c(s1,s2),c(s1,s2))
st.sp
pot.info <- make.gRbase.potentials(mc, node.names = gp@nodes)
f0 <- function(y){ as.numeric(c((y==1),(y==2)))} # Feature function
# Check and see if Pr(X) ~= prod Pr(Xi|X/Xi)
en.dist.info <- distribution.from.energies(st.sp, mc$edges, pot.info$node.energies, pot.info$edge.energies, config.energy, f0)
en.dist <- cbind(st.sp,en.dist.info$state.probs)
en.dist
pl.dist.info <- pseudolikelihoods.from.energies(
st.sp, adjacent.nodes = mc$adj.nodes,
edges.mat = mc$edges,
node.energies = pot.info$node.energies,
edge.energies = pot.info$edge.energies,
conditional.energy.func = conditional.config.energy,
ff = f0)
cbind(100*round(en.dist[,5],3), 100*round(pl.dist.info$pseudo.likelihoods,3))
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