Nothing
`Mrandom` <-
function(x,shape,scale,prior,K)
{
lik <- NULL
for (k in 1:K) {
shape.vec <- shape[k,]
scale.vec <- scale[k,]
prior.vec <- prior[k,]
likmat <- t(apply(x,1,function(y){
la.vec <- prior.vec*(dweibull(y,shape.vec,scale.vec)) #pages visited by session
la.vec[is.na(la.vec)] <- 0
la.vec[la.vec==0|la.vec==Inf] <- 1-prior.vec[la.vec==0|la.vec==Inf] #dweibull either 0 or Inf for 0 dwell time (pages not visited by session)
return(la.vec)
}))
#likmat <- log(likmat)
#lik <- cbind(lik,apply(likmat,1,sum)) #multiplying prob over pages
lik <- cbind(lik,apply(likmat,1,prod)) #multiplying prob over pages
}
lik.n <- log(apply(lik, 1, max)) #maximum log-likelihood value for each session
#lik.n <- apply(lik, 1, max) #maximum log-likelihood value for each session
lik.tot <- sum(lik.n)
denom <- apply(lik,1,sum) #denominator for posterior
postmat <- apply(lik,2,function(y) {y/denom}) #posterior matrix of dimension n x K
newgr <- apply(postmat,1, function(y) {((1:K)[y==max(y)][1])}) #randomized cluster assignment
list(newgr=newgr,lik.tot=lik.tot,postmat=postmat)
}
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.