similar to: passing variable to formula environment

Dear all, This is a rather lengthy message, but I don't know what I made wrong in my real example since the simple code works. I have two variables a, b and a function f for which I would like to calculate all possible combinations of the values of a and b. If f is multiplication, I would simply do: a <- 1:5 b <- 1:5 outer(a,b) ## A bit more complicated is this: f <-

Dear all, This is a rather lengthy message, but I don't know what I made wrong in my real example since the simple code works. I have two variables a, b and a function f for which I would like to calculate all possible combinations of the values of a and b. If f is multiplication, I would simply do: a <- 1:5 b <- 1:5 outer(a,b) ## A bit more complicated is this: f <-

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) :

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, 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) {

Hola a tod en s, bueno, un poco al hilo de un mensaje anterior, reformulo la pregunta y pongo código completamente reproducible, a ver si hay más suerte. Estoy con un informe y hay que hacer algunos gráficos con datos diferentes con ggplot2, y hay que poner el mismo tamaño para todos ellos. El problema es que R cambia automáticamente el tamaño del área de trazado y el margen en función de

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))

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'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:

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, I am plotting many histograms together using facet_grid in ggplot2. However, I want to then add a vertical line to each histogram, or facet, each of which vertical lines are at different x-values. The following example adds all vertical lines to each facet: ggplot(data,aes(values)) + geom_histogram() + facet_grid(.~variable) + geom_vline(xintercept=c(5,10,15)) How can I add a vertical

> 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

Just as an exercise I am tying to add colours to a geom_segment command. I can get one colour but not a sequence of colours. Can anyone suggest how I can get the green lines in the plot below to be different colours? I thought I could use a palatte of colours but that did not seem to work. Thanks ========================================================================= library(ggplot2) xx

On Tue, Mar 22, 2011 at 1:36 PM, Gokul Ramaswamy <gokulhcramaswamy at gmail.com > wrote: > 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

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

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

On 03/22/2011 01:56 PM, Reid Kleckner wrote: > On Tue, Mar 22, 2011 at 1:36 PM, Gokul Ramaswamy > <gokulhcramaswamy at gmail.com <mailto:gokulhcramaswamy at gmail.com>> wrote: > > 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

Hi Alexandra, I don't know much, maybe this topic should be bridged with polly-dev (adding it to CC) to bring it more attention. Indeed, polly uses ScopPass, that creates serious limitations in compatibility with other passes. To my understanding, scops are used because ISL loop analysis tool uses scops. In fact, just for handling OpenMP directives scops are not required, unless one need to

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.