Nothing
`mcmcProc` <-
function(v, N, thin, burn.in, comp.list, verbose=TRUE)
{
if(is.null(thin))
thin = 20 # default value for thinning
if(is.null(burn.in))
burn.in=N # default value for burn.in
n <- nrow(v)
k <- ncol(v)
M <- (N+burn.in)*thin
samples <- matrix(0,N,k)
ind <- 1
# start with the best candidate
last <- rep(0,n)
excl <- n+1
for(j in 1:k){
last[j] <- rmult(1, (1:n)[-excl], v[,j][-excl])
excl <- last[1:j]
}
last[(k+1):n] <- sample((1:n)[-last[1:k]], n-k)
#last <- comp.list[sample(1:n,n)]
vs <- sample(1:k, M, replace=TRUE)
hs <- sample(1:n, M, replace=TRUE)
unifs <- runif(M)
if(verbose)
cat("MCMC: ")
for (i in 1:M)
{
x <- last
vert <- vs[i]
horz <- hs[i]
temp <- last[vert]
x[vert] <- last[horz]
x[horz] <- temp
if(horz > k)
A <- v[x[vert],vert]/v[last[vert],vert]
else
A <- v[x[vert],vert]*v[x[horz],horz]/
(v[last[vert],vert]*v[last[horz],horz])
if (A > unifs[i]){
if(i%%thin==0 && i>=burn.in*thin)
samples[i/thin-burn.in,] <- x[1:k]
last <- x
}
else
if(i%%thin==0 && i>=burn.in*thin)
samples[i/thin-burn.in,] <- last[1:k]
if(i%%(M/10)==0 && verbose)
cat(paste(i*100/M, "% ",sep=""))
}
samples
}
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