similar to: outer-question

> From: Thomas Lumley > > On Sun, 30 Oct 2005, Jonathan Rougier wrote: > > > I'm not sure about this. Perhaps I am a dinosaur, but my feeling is > > that if people are writing functions in R that might be subject to > > simple operations like outer products, then they ought to be writing > > vectorised functions! > > I would agree. How about an

List gurus, I'm trying to code a Gompertz growth curve function as part of a larger project and have run across a problem due to my ignorance of environments. Some sample data and the function are as follows: growth <- data.frame(age = c(1.92, 3, 5.83, 3.17, 15.5, 1.17, 5.58, 13.33, 14.29, 5.83, 13.79, 6.33, 13.75, 16.83, 13, 11.67, 0.25, 1.73, 9.46, 5.67), length = c(157, 165, 179,

Sorry, I just realized I didn't type in the correct names of the variables I am working with, this is how it should be: plot(1,1,type="n") for (i in summ$tx) { points(summ$timep[summ$tx==i],summ$mn[summ$tx==i]) lines(summ$timep[summ$tx==i],summ$mn[summ$tx==i]) } Thank you, Judith ____________________________________________________________________________________

Hi, I have a problem with fitting a nonlinear mixed-effects model to my data. I was able to fit quite simple exponential model but now I?m trying to fit the following Gompertz model: > gomp<-nlme(paino~b0+b1*exp(-exp(-b2*(daydeg.scale-b3))), data=group1, fixed=b0+b1+b2+b3~1, start=c(b0=150, b1=3000, b2=0.6, b3=2500)) I?m getting the following error: Error in chol((value + t(value))/2) :

Hello, Information: gcc -v: gcc version 4.3.3 (Debian 4.3.3-3) os: Debian/Testing Pulled latest release from asterisk site, compiled, installed it. I have a barebones configuration: $ ls -l asterisk extensions.conf modules.conf sip.conf users.conf voicemail.conf You can see them here: http://home.comcast.net/~jpiszcz/20090418/extensions.conf

Hi all, Sorry if this has been answered already, but I couldn't find it in the archives or general internet. Is it possible to implement the gompertz distribution as survreg.distribution to use with survreg of the survival library? I haven't found anything and recent attempts from my side weren't succefull so far. I know that other packages like 'eha' and

Dear list: I am attempting to use what I thought would be a pretty straightforward practical application of Cox regression. I figure users of the survival package must have come across this problem before, so I would like to ask you how you dealt with it. I have set up an illustrative example and included it at the end of this post. I took a sample of 100 data points from each of two populations

Hello, I'm trying samba-2.0.6 on my Sony NEWS-OS 4.2.1aRD which is based on 4.3BSD, having trouble with compilation. Also I have question and want be helped to solve the problem. Yes, I can compile it with dirty hack which is found at ftp://ftp.tutrp.tut.ac.jp/pub/sony-news/samba/samba-news4.diff There are some problems about this old and specific system. 1. It does not have setvbuf(). 2.

Hello, all. I have co-opted a number of functions that can be used to plot the hazard/survival functions and associated density distribution for a Gompertz mortality model, given known parameters. The Gompertz hazard model has been shown to fit relatively well to the human adult lifespan. For example, if I wanted to plot the hazard (i.e., mortality) functions: pop1 <- function (t) {

Hi- I'm a biologist trying to figure out the growth rate of salamanders in different ponds. I collected individuals from various populations at different dates, and using the size and date collected, I want to figure out the growth curve of each population. My question is: How do I fit my data to a Gompertz function in R? Thank you so much! Sarah -- View this message in context:

Dear all! I tried to fit Gompertz growth models to describe cummulative germination rates using nls. I used the following code: germ.model<-nls(percent.germ~a*exp(-b*exp(-k*day)),data=tab,start=list(a=100,b=10,k=0.5)) My problem is that I want that the fitted model goes through the origin, since germination cannot start before the experiment was started, and y-max should be 100. Does anyone

Changes: * Removed utimes() posix hack since scp.c moved to utimes() * Fixed waitpid() to be more proper. It was driving me nuts. * Made setsid() a #define in next-posix.h * Removed WCOREDUMP() from next-posix.h since we really don't support it and now #ifdef .. #else .. #endif around the single place it was used. * Fixed typecasting issue in sshd.c with sizeof() returning "long

Dear All, I would like to fit some parametric survival models using left truncated, right censored data in R. However I am having problems finding a function to fit parametric survival models which can handle left truncated data. I have tested both the survreg function in package survival: fit1 <- survreg(Surv(start, stop, status) ~ X + Y + Z, data=data1) and the psm function in package

Dear Sir/ Madam, I'm having trouble de-bugging the following - which works perfectly well with optim or optimx - but not with mle2. I'd be really grateful if someone could show me what is wrong. Many thanks in advance. JSC: gompertz<- function (x,t=data) { a3<-x[1] b3<-x[2] shift<-data[1] h.t<-a3*exp(b3*(t-shift))

On Feb 6, 2008, at 5:18 AM, Duncan Sands wrote: > Hi, > >> if /bin/sh ./libtool --mode=compile /s/llvm/obj.gcc42/./gcc/xgcc -B/ >> s/llvm/obj.gcc42/./gcc/ -B/usr/local/i686-pc-linux-gnu/bin/ -B/usr/ >> local/i686-pc-linux-gnu/lib/ -isystem /usr/local/i686-pc-linux-gnu/ >> include -isystem /usr/local/i686-pc-linux-gnu/sys-include - >> DHAVE_CONFIG_H -I.

Hi Duncan Sands, As I have understood, GOMP and OpenMP provides support for parallelizing program at source program level. But I am at the IR level. That is I am trying to parallelize the IR code. This is the case of automatic parallelization. The programmer writing the code does not have any idea of parallelization going behind the hood. So my question is instead of support at the source

Hello R-gurus, I'm trying to adjust different growth curves to a rather extensive dataset. I wrote up a function to go through all of them, but am encountering a problem : among the more than 1000 curves I have, obviously for some of them I encounter conversion problems. I'd like for my function to keep going to the next curve and store the fact that for curve number X I had a convergence

Hi, I want to execute the iterations of a loop in parallel, by inserting calls either to pthreads or to the gomp library at the LLVM IR level. As a first step, I inserted an omp pragma in a C file and compiled it with llvm-gcc to check the generated LLVM code. If I understand correctly, to parallelize the loop in LLVM IR, I have to separate the loop in a new function, put all required parameters

Hi, I need a help to know whether I can perform the following in R: I have a set of observations (Ns) and each observation is drawn from a poisson distribution with an unkown mean, lambda. The set of lambdas in their turn are drawn from a common prior distribution which is supposed to be a a mixture of two gamma distributions. Is there a way to determine the poisson means in R, given the Ns and

Hi, I would like to ask which version of OpenMP is supported by DragonEgg and at which extent(i.e. fully, partially etc.).