similar to: number of copies

Dear Thomas & Dear List, the fitting function `coxph.fit' called by `coxph' may fail to estimate the regression coefficients when some values of the design matrix are very large. For example library(survival) ### load example data load(url("http://www.imbe.med.uni-erlangen.de/~hothorn/coxph_fit.Rda")) method <- "efron" ### copied from `coxph.fit' coxfit

Hi, I want to fit multiple cox models using the coxph() function. To do this, I use a for-loop and save the relevant results in a separate matrix. In the example below, only two models are fitted (my actual matrix has many more columns), one gives a warning message, while the other does not. Right now, I see all the warning message(s) after the for-loop is completed but have no idea which model

Hi there, Here is a record of an R session: > library(survival4) Autoloading required package: splines > coxph(Surv(c(1,2,3,4), c(1,1,1,1)) ~ c(1,0,1,0)) Error in .C("coxfit2", iter = as.integer(iter.max), as.integer(n), as.integer(nvar), : C/Fortran function not in load table Why is "coxfit2" not in the load table? How do I fix it? System is Linux. Goran

R CMD check tells me * checking R code for possible problems ... NOTE agexact.fit.rds: ... may be used in an incorrect context: ?optim(init, agfitfn, ...)? Warning: <anonymous>: ... may be used in an incorrect context: ?optim(init, agfitfn, ...)? Can anyone tell me what this message means? My searches haven't turned up anything useful. This is with R 2.7 and 2.9. The message

Hello, coxph does not use any information that are in the dataset between event times (or "death times") , since computation only occurs at event times. For instance, removing observations when there is no event at that time in the whole dataset does not change the results: > set.seed(1) > data <- as.data.frame(cbind(start=c(1:5,1:5,1:4),stop=c(2:6,2:6,2:5),status=c(rep(

Dear all, I am using Windows and R 2.9.2 for my analyses. I have a large dataset and I am particularly interested in looking at time to an event for a continuous variable. I would like to produce a plot of log(relative risk) or relative risk (also known as hazard ratio) against the continuous variable. I have spent a long time looking for advice on how to do this but my search has proved

All, I am struggling to create a survival plot using LTRC data for each year of a 10 year period. I have a set of individuals (birds) where 'entry' is the day of the year (1-365) they are released (let out of pens) into the wild (2 year data snip below). 'Entry' (e.g., day of year the first bird is released for each year) is highly variable, ranging from 48 to >250. When I

My understanding is that R will not make copies of lists if there is only one reference to the object. However, I've encountered a case where R does make copies, even though (I think) there should be only one reference to the object. I hope that someone could shed some light on why this is happening. I'll start with a simple example. Below, x is a list with one element, and changing that

Full_Name: Jerome Asselin Version: 1.6.1 OS: RedHat Linux 7.2 Submission from: (NULL) (142.103.173.179) Hello, I get a segmentation fault when I run the following code. I wouldn't expect meaningful results because my response variable contains only missing values. However, I would expect something like a regular error (not a segmentation fault). library(survival) data <-

Hello, I'm trying to estimate a cox model with a frailty variable and time-dependent covariate (below there is the statement I use and the error message). It's seems to be impossible, because every time I add the time-dependent covariate the model doesn't converge. Instead, if I estimate the same model without the time-dependent covariate it's converge. I'd like knowing if

Hello everybody. First of all, I would like to present myself. I'm a french student in public health and I like statistics though I'm not that good in mathematics (but I try to catch up). I've discovered R recently while trying to find a statistical program in order to avoid rebooting my computer under windows when I need to do some statistical work. And here is my first question.

Hello, I am new to R on Linux (and to LINUX), running a 1.9.1 on a Linux MDK10.0. When updating or installing different packages, I get messages like this (under), the package doesn't install. Can anyone help me? I know this is all to little information, but I don't know were to start. I think there is something wrong in how or were the C++ or fortran compilator is installed?? Thanks, Geir

---------------------------- Original Message ---------------------------- Subject: Different results from survreg with version 2.6.1 and 2.10.1 From: nathalcs at ulrik.uio.no Date: Fri, March 19, 2010 16:00 To: r-help at r-project.org -------------------------------------------------------------------------- Dear all I'm using survreg command in package survival.

Hi Expert I want to use dtrace to monitor the content change of one file. I made following scripts, #!/usr/sbin/dtrace -s inline int MYPID = $1; syscall::write:entry /pid == MYPID/ { tracemem(arg1, arg2); printf("\n"); } It always has an following error bash-3.00$ sudo dumpFIFO.dtrace 3836 dtrace: failed to compile script ./dumpFIFO.dtrace: line 19: tracemem( ) argument #2

Hi, I've noticed that as.vector() always allocates a new object, e.g. > x <- 1:10; > x <- as.vector(x); > tracemem(x); [1] "<0x0000000005622db8" > x <- as.vector(x); tracemem[0x0000000005622db8 -> 0x0000000005622ec0]: as.vector > x <- as.vector(x); tracemem[0x0000000005622ec0 -> 0x0000000005622f18]: as.vector > x <- as.vector(x);

Hi All, i have a problem in understanding what the assignment operator '<-' really is doing. If i create two numeric arrays in R and copy one into the other with '<-' and afterwards change one array by calling a C function, both arrays are changed! The problem I am facing can easily be seen in the following example: (The following R code and the C function is attached and

N_conreq:entry { self->x=1; calledaddr=(struct xaddrf *)arg3; callingaddr=(struct xaddrf *)arg4; trace(calledaddr->link_id); tracemem(calledaddr->DTE_MAC.lsap_add, 80); trace(callingaddr->link_id); tracemem(callingaddr->DTE_MAC.lsap_add, 80); } 0 -> N_conreq 255

Hi all, I've been trying to get a better handle on what manipulations lead R to duplicate a vector, creating small experiments and using tracemem to observe what happens (all in 2.15.1). That's lead me to a few questions, illustrated using the snippet below. x <- 1:10 tracemem(x) # [1] "<0x1058f8238>" x[5] <- 5 # tracemem[0x1058f8238 -> 0x105994ab0]: x[11] <-

I've been playing with passing arguments to .C(), and found that replacing as.double(x) with if(is.double(x)) x else as.double(x) saves time and avoids one copy, in the case that x is already double. I suggest modifying as.double to avoid the extra copy and just return x, when x is already double. Similarly for as.integer, etc. [[alternative HTML version deleted]]

Hello all, A friend recently brought to my attention that vector assignment actually recreates the entire vector on which the assignment is performed. So for example, the code: x[10]<- NA # The original call (short version) Is really doing this: x<- replace(x, list=10, values=NA) # The original call (long version) # assigning a whole new vector to x Which is actually doing this: x<-