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CentOS Errata and Security Advisory CESA-2008:0214 squid security update for CentOS 3 i386: https://rhn.redhat.com/errata/RHSA-2008-0214.html The following updated file has been uploaded and is currently syncing to the mirrors: i386: updates/i386/RPMS/squid-2.5.STABLE3-9.3E.i386.rpm source: updates/SRPMS/squid-2.5.STABLE3-9.3E.src.rpm You may update your CentOS-3 i386 installations by running

CentOS Errata and Security Advisory CESA-2008:0214 squid security update for CentOS 3 x86_64: https://rhn.redhat.com/errata/RHSA-2008-0214.html The following updated file has been uploaded and is currently syncing to the mirrors: x86_64: updates/x86_64/RPMS/squid-2.5.STABLE3-9.3E.x86_64.rpm source: updates/SRPMS/squid-2.5.STABLE3-9.3E.src.rpm You may update your CentOS-3 x86_64 installations

CentOS Errata and Security Advisory 2008:0214 https://rhn.redhat.com/errata/RHSA-2008-0214.html The following updated files have been uploaded and are currently syncing to the mirrors: s390: updates/s390/RPMS/squid-2.5.STABLE3-9.3E.s390.rpm s390x: updates/s390x/RPMS/squid-2.5.STABLE3-9.3E.s390x.rpm -- Pasi Pirhonen - upi at iki.fi - http://pasi.pirhonen.eu/ Top-postings silently ignored

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I compiled the 1.9.1 src.rpm with the standard gnu tools and it works. I tried compiling the 1.9.1 src.rpm with the Intel 8 C and FORTRAN compilers and it bombs out during the testing phase: comparing 'd-p-q-r-tests.Rout' to './d-p-q-r-tests.Rout.save' ...267c267 < df = 0.5[1] "Mean relative difference: 5.001647e-10" --- > df = 0.5[1] TRUE

Dear list members, I am trying to estimate parameters of the AR(1)-GARCH(1,1) model. I have one additional dummy variable for the AR(1) part. First I wanted to do it using garchFit function (everything would be then estimated in one step) however in the fGarch library I didn't find a way to include an additional variable. That would be the formula but, as said, I think it is impossible to add

Dear all, Does the frailty.object$history[[1]]$theta returns the Variance of random effect? Why is the value different? Here is an example with kidney data: > library(survival) > data(kidney) > frailty.object<-coxph(Surv(time, status)~ age + sex + disease + frailty(id), kidney) > frailty.object Call: coxph(formula = Surv(time, status) ~ age + sex + disease + frailty(id), data

Hi, I'm trying to using pspline in bic.surv{BMA}. ############################# library(BMA) library(survival) data(veteran) test.bic.surv<- bic.surv(Surv(time,status) ~ karno+pspline(age,df=3)+diagtime+prior, data = veteran, factor.type = TRUE) summary(test.bic.surv, conditional=FALSE, digits=2) ############################# The results are:

CentOS Errata and Security Advisory 2008:0214 https://rhn.redhat.com/errata/RHSA-2008-0214.html The following updated files have been uploaded and are currently syncing to the mirrors: ia64: updates/ia64/RPMS/squid-2.5.STABLE3-9.3E.ia64.rpm -- Pasi Pirhonen - upi at iki.fi - http://pasi.pirhonen.eu/ Top-postings silently ignored -------------- next part -------------- A non-text attachment

Hi everybody, I'm trying to fit a Garch(1,1) process to the DAX returns. My data consists of about 2300 10day-logreturns in chronologically descending order (see attachment). But if I use the garch function I get a very high alpha_1 and a quite low beta, which doesn't make that much sense. I think I am missing something, but have no idea what it might be. I'd appreciate it a lot

Hello R-users, I have been trying to fit what I think is a simple mixed-effects model using lmer (from lme4), but I've run into some difficulty that I have not been able to resolve using the existing archives or Pinheiro and Bates (2000). I am measuring populations (of birds) which change with time at a number of different sites. These sites are grouped into regions. Sites are not measured