search for: tstarting

Hello! I'm looking for an easy way to filter data frames. Some rows in my data frame needs to be left out, for instance, rows with invalid data. Right now, if I want to pair two columns of this data frame, I have to do this: > pairs(as.data.frame(list(tstart=df$tstart[valid],tend=df$tend.sdr[valid]))) or this: >

Hi everyone, I was trying to mode the following exercise using R. The question: Set up a one pool model using numericintegration. The model will run from time 1 to time 30 using a time step of 1.The pool (A) will be fed by flux "inA" at a rate of 5 units per hour anddrained by flux "outA" at a rate of 20% per hour. At time 0, A has 5units. At time 30, what is the pool size of

in wine/dlls/qcap/v4l.c: ReadThread() --> OutputPin_GetDeliveryBuffer((OutputPin *)capBox->pOut, &pSample, NULL, NULL, 0); --> IMediaSample_SetTime(*ppSample, tStart, tStop); in wine/dlls/quartz/memallocator.c: StdMediaSample2_GetTime(IMediaSample2 * iface, REFERENCE_TIME * pStart, REFERENCE_TIME * pEnd) --> if tstart/stop is NULL, leave pStart/pEnd not setted. in

  Hi there,   I am beginner in R and I have some basic question. Suppose I run a common procedure such as a t test or cox model like below:   out<-coxph( Surv(tstart,tstop, death1) ~ x1+x1:log(tstop+1) , test1,method=c("breslow"))    Which yields the following result:   Call: coxph(formula = Surv(tstart, tstop, death1) ~ x1 + x1:log(tstop +     1), data = test1, method =

Dear All, I got a warning message "X matrix deemed to be singular" in Cox model with a time dependent coefficient. In my analysis, the variable "SEX" is a categorical variable which violate the PH assumption in Cox. I first used the survSplit() function to break the data set into different time intervals, and then fit the model. The procedures can be described as follows:

tftp-hpa-0.35 and tftp-hpa-0.36 show wrong transmission time. >tftp -V tftp-hpa 0.36, with readline >tftp -m octet -v localhost -c get aaa /tmp/aaa Connected to localhost.localdomain (127.0.0.1), port 69 getting from localhost.localdomain:aaa to /tmp/aaa [octet] Received 33554432 bytes in -3.3 seconds [-81407477 bit/s] ^^^^ ^^^^^^^^^ By the way, why

I have data that looks like this time_stamp (seconds) user_id The data is (partial) ordered by time - in that sometimes transactions occur at the same timestamp. The output I want is collated by transaction time on a per user basis, normalized by the maximum number of transactions per user, and aggregated over each day. So, if the users have 50 transactions in the first day and 20 transactions

Hi, I want to read a text file into R with .Call(). So I define some NEW_CHARACTER() to store the chracters read and use SET_STRING_ELT to fill the elements. e.g. PROTECT(qNames = NEW_CHARACTER(10000)); char *foo; // This foo holds the string I want. while(foo = readLine(FN)){ SET_STRING_ELT(qNames, i, mkChar(foo))); } In this way, I can get the desired character from qNames. The only problem

Hi there, I have a rather large data set and perform the following cox model: test1 <- list(tstart,tstop,death1,chemo1,radio1,horm1) out1<-coxph( Surv(tstart,tstop, death1) ~ chemo1+chemo1:log(tstop+1)+horm1+horm1:log(tstop+1)+age1+grade1+grade1:log(tstop+1)+positive1+positive1:log(tstop+1)+size1+size1:log(tstop+1), test1) out1 Up to here everything works fine (with each covariate

Hello, I have a cohort with approx 1,200 patients at the ages of 30-65 that had their first myocardial infarction during 1992: · They were in a follow up until 2005. · About 400 of them died during this period of time (right censored) · Each one of them had up to 4 mi recurrent events. I am using the semi-parametric model in order to assess the relationship of

Hi all, Sometimes the process cdrommon use 99,8% of CPU and the result is that all vms becames very slow. I killed the process and now everything is fine but I can''t live migrate VMS. I found this problem also in this citrix thread: http://forums.citrix.com/thread.jspa?messageID=1475962 <http://forums.citrix.com/thread.jspa?messageID=1475962&tstart=0#1475962>

Hi all, Issue: I merged two zoo objects (a regular and an irregular). After the merge I used the function 'na.approx' to have also values in the resolution of the regular time series. Problem: After approximation some rows at the beginning or at the end of the zoo objects disappear due to the 'na.approx' algorithm. Now I just want to have all the rows of the regular time series

Hi, when i run the following code i get this massege: "The instruction at 0x######## reference memory at 0x#######, the memory cannot be "read". and then i have to close R. what is the problem and how can i solve it? thanks in advance Avi my code # frailtypack library(frailtypack) cgd.ag <- read.csv("C:/rfiles/RE/cgd.csv") cgd.nfm <-frailtyPenal(Surv(TStart,

Hi , I have a data set with recurrence time (up to four) of myocardial infarction (MI). Part of the file is showing below: Num1 Trt Sex Time T1 T2 T3 T4 1011 1 1 9 1211 0 1 59 3020 1 2 14 3 1245 0 1 18 12 16 3069 1 2 26 6 12 13 2051 0 1 53 3 15 46 51 The data consist of the following eight variables: Num1 , patient number Trt, treatment group (1=placebo and 2=drug) Sex,

Hi, Sorry not to provide R-code in my previous mail. R code is below #install.packages("rms") require(rms) #install.packages("mstate") library(mstate) require(splines) library(ggplot2) library(survival) library(splines) #install.packages("survsim") require(survsim) set.seed(10) df<-crisk.sim(n=500, foltime=10, dist.ev=rep("lnorm",2),

I frequently see this from my iPhone/iPad IMAP users: Oct 24 21:30:55 server dovecot: imap-login: Login: user=<user>, ... [... repeated 10 times ...] Oct 24 21:32:54 server dovecot: imap-login: Maximum number of connections from user+IP exceeded (mail_max_userip_connections=12): user=<user> Oct 24 21:32:54 server dovecot: imap(user): Logged out ... [... repeated 11 times

Hi Nicolas, 2009/3/30 Nicolas Geoffray <nicolas.geoffray at lip6.fr> > Can you be more verbose on this? Are you planning to implement some JVM > or .Net extension for supporting your new intrinsics? Or are you just > looking for a runtime with a GC? At the moment I am not looking to add any new extensions to JVM or .NET. I would need a runtime with a GC to demonstrate and test

I can't comment on frailtypack issues, but would like to mention that coxme will handle nested models, contrary to the statement below that "frailtypack is perhaps the only .... for nested survival data". To reprise the original post's model cgd.nfm <- coxme(Surv(Tstart, Tstop, Status) ~ Treatment + (1 | Center/ID), data=cgd.ag) And a note to the poster-- you should

Has anybody tried to use Rmpi with the OpenMPI library instead of LAM/MPI? LAM appears to be somewhat hardcoded in the Rmpi setup. Before I start to experiment with changing this, has anybody else tried Rmpi with non-LAM MPI implementations? Dirk -- Hell, there are no rules here - we're trying to accomplish something. -- Thomas A. Edison

I haven't done any R memory debugging lately, but https://www.mail-archive.com/rcpp-devel at lists.r-forge.r-project.org/msg10289.html shows how I used to have gdb break where valgrind finds a problem so you could examine the details. Also, running your code after running gctorture(TRUE) can help track down memory problems. -Bill On Wed, Feb 7, 2024 at 12:03?PM Therneau, Terry M., Ph.D.