similar to: Hazard model with long-term survivor (cure model)

Dear R-users, I have a couple of questions about the relsurv package: 1) when I try to run the example: fit <- rsmul(Surv(time,cens)~sex+as.factor(agegr)+ratetable(age=age*365.24,sex=sex,year=year),ratetable=slopop,data=rdata) with the datasets in the package (rdata and slopop) it gives me an error: Error in nrow(x) : object "x" not found 2) If I have a date format

Dear All, Does someone have, or know of survexp ratetables for european contries, especially Austria and Germany? I know only about slopop in the package relsurv. Thanks in advance Heinz T??chler

Dear R-Users, I've recently used relsurv package for relative survival analysis. In particular I've tried to reproduce the examples proposed in the R-documentation about rsadd, rsmul and rstrans functions in R latest version (R 2.14.1). These examples don't run and the error message is always the following: data(slopop) data(rdata)

Hi all, May i know does R has packages or code to run "Bayesian Relative Survival Analysis"? I have look through Bayesian Survival Analysis(2001) by Joseph George Ibrahim<http://www.google.com/search?tbo=p&tbm=bks&q=inauthor:%22Joseph+George+Ibrahim%22>, Ming-Hui Chen<http://www.google.com/search?tbo=p&tbm=bks&q=inauthor:%22Ming-Hui+Chen%22>, Debajyoti

Two questions: I have a lot of data for which the last of each of the repeated individual obserations is censored. Apart from the suite in survival, which seems to be very complex to a new R user, is there any other simple function that exists in CRAN library (I have most of these but haven't found one!) that is essentially the same as lm() but with an additional censor argument (vector of

Dear All, I am desperately trying to find any R package that fits a mixture survival models also know as a cure models. These are survival models where the survival function is improper, which also means that a fraction of subjects are expected not to expreience the event. A huge literature has been developed for these type of models but I couldn't find any R package that fits them.

Hi all, Following the lines of Red Hat's announcement for commitment for better open-source model, along with many other companies (lead by Facebook/Google/IBM) [1], Gluster project is also proposing to have the COMMITMENT statement in its project. While we discuss about the same here, a RFC patch is submitted to review. [2] [1] -

On Thu, 10 Aug 2017, Gary Stainburn wrote: > I have the following error message in my /var/log/spamd > > spf: lookup failed: available_nameservers: No DNS servers available! > > Having Googled the error message I've found a number of responses > which involve patching Perl or Spamassassin or other cures. > > Before I start changing things I was wondering if there

On 08/10/2017 01:21 AM, Gary Stainburn wrote: > I have the following error message in my /var/log/spamd > > spf: lookup failed: available_nameservers: No DNS servers available! Try starting spamassassin later. Run "systemctl edit spamassassin.service" and insert two lines: [Unit] After=network-online.target

On 10/08/17 15:37, Paul Heinlein wrote: > On Thu, 10 Aug 2017, Gary Stainburn wrote: > >> I have the following error message in my /var/log/spamd >> >> spf: lookup failed: available_nameservers: No DNS servers available! >> >> Having Googled the error message I've found a number of responses >> which involve patching Perl or Spamassassin or other

On Thursday 10 August 2017 18:45:32 Gordon Messmer wrote: > On 08/10/2017 01:21 AM, Gary Stainburn wrote: > > I have the following error message in my /var/log/spamd > > > > spf: lookup failed: available_nameservers: No DNS servers available! > > Try starting spamassassin later. Run "systemctl edit > spamassassin.service" and insert two lines: > >

Dear All, I am desperately trying to find any R package that fits a mixture survival models also know as a cure models. This are survival model where the survival function is improper which also means that a fraction of subjects are expected not to expreience the event. A Huge literature has been developed for thes type of models but I couldn't find any R package that fits this type of

Hello all, I am using AddHealth data to fit a cure, aka split population model using nltm. I am not sure how to account for the complex survey design - does anyone have any suggestions? Any help would be greatly appreciated! Sincerely, Sam

Hi, this method for block SSH Login Attack it seems to be good. http://www.soloport.com/iptables.html which it is the better way in order to implement it into shorewall config files? Many thanks -- Dario Lesca <d.lesca@solinos.it>

Hi, I tried to do a nested Anova with the attached Data. My response variable is "survivors" and I would like to know the effect of (insect-egg clutch) "size", "position" (of clutch on twig) and "clone" (/plant genotype) on the survival of eggs (due to predation). Each plant was provided with three different sizes of clutches (45,15,5) and had

Hello, We're seeing lots of warnings like the following, running Asterisk 1.6.1.12. Does anyone know the cause or cure? One explanation I've come across is that the peer is congested and sending RTCP messages asking us to slow the RTP down. Is there any way we can verify this? [May 17 13:42:45] WARNING[27482] channel.c: Exceptionally long voice queue length queuing to Local/12126412121

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I have the following error message in my /var/log/spamd spf: lookup failed: available_nameservers: No DNS servers available! Having Googled the error message I've found a number of responses which involve patching Perl or Spamassassin or other cures. Before I start changing things I was wondering if there was a Centos 7 specific resolution. Where possible, on production machines I prefer

Hello All, I mentioned a problem with this once before, and was referred to other threads that also talked about this. But I believe a recent problem I was experiencing, may have been related to this: [: -le: argument expected. So I'd like to bring it up again, in hopes that someone might have a cure. Specifically, two printf()'s are sent to the same line, which results in a /very/ hard

I extracting splitting rules from Greg Ridgeway's GBM 1.6-3.2 in R 2.15.2, so I can run classification in a production system outside of R. ?I have it working and verified for a dummy data set with all variable types (numeric, factor, ordered) and missing values, but in the titanic survivors data set the splitting rule for factors does not make sense. ?The attached code and log below explains