Displaying 4 results from an estimated 4 matches for "iniziale".
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initiale
2012 Feb 17
4
xen-unstable unable to boot on Wheezy
...9;'
echo ''Caricamento Hypervisor Xen 4.2...''
multiboot /boot/xen.gz placeholder dom0_mem=1024M
echo ''Caricamento Linux 3.2.0-1-amd64...''
linux /boot/vmlinuz-3.2.0-1-amd64 placeholder root=/dev/mapper/RAID-ROOT ro
quiet
echo ''Caricamento ramdisk iniziale...''
initrd /boot/initrd.img-3.2.0-1-amd64
}
-----------------------------------------
I try also with debug options and see with SOL (serial on lan) if see some
more but also with it see only the three echo line.
The grub2 entry is:
-----------------------------------------
menuentry ...
2008 Mar 13
0
help with summary(polr_model)
...r, envir, enclos) :
> non-integer #successes in a binomial glm
Then when I try to summarize the model, in order to use xtable
> summary(base.op)
> Re-fitting to get Hessian
> Errore in optim(start, fmin, gmin, method = "BFGS", hessian =
> Hess, ...) :
> valore iniziale in 'vmmin' non finito
that freely translated to english means "starting value in
'vmmin' not finished (or finite, more likely)"
what does this mean? How can I have my summary?
Thank you
Luca
--
Luca Braglia, aka Bragliozzo
http://braglio...
2009 May 22
0
EM algorithm mixture of multivariate
..., log=FALSE)
f2<-dmvnorm(y, mu02, sd02, log=FALSE)
p=alpha0*f1+(1-alpha0)*f2
scatterplot3d(y[,1], y[,2], p , highlight.3d=TRUE, col.axis="blue",
col.grid="lightblue",main="val iniz mistura normali multivariata",
angle=120, pch=20)
#verosimiglianza iniziale
l0<-sum(log(p))
l1<-l0
alpha<-alpha0
mu1<-mu01
mu2<-mu02
sd1<-sd01
sd2<-sd02
for (iter in 1:itermax)
{
#passo E
for (i in 1:n) {
tau[i,1]<-(alpha*f1[i])/p[i]
tau[i,2]<-((1-alpha)*f2[i])/p[i]
}
#passo M
alpha= mean(tau[,1])
mu1=colSums(tau[,1]*y)/sum(tau[,1])
mu2=c...
2009 May 22
0
EM algorithm mixture of multivariate gaussian
..., log=FALSE)
f2<-dmvnorm(y, mu02, sd02, log=FALSE)
p=alpha0*f1+(1-alpha0)*f2
scatterplot3d(y[,1], y[,2], p , highlight.3d=TRUE, col.axis="blue",
col.grid="lightblue",main="val iniz mistura normali multivariata",
angle=120, pch=20)
#verosimiglianza iniziale
l0<-sum(log(p))
l1<-l0
alpha<-alpha0
mu1<-mu01
mu2<-mu02
sd1<-sd01
sd2<-sd02
for (iter in 1:itermax)
{
#passo E
for (i in 1:n) {
tau[i,1]<-(alpha*f1[i])/p[i]
tau[i,2]<-((1-alpha)*f2[i])/p[i]
}
#passo M
alpha= mean(tau[,1])
mu1=colSums(tau[,1]*y)/sum(tau[,1])
mu2=c...