similar to: Writing R package and do.call

Hello R-help, I've noticed that my 'parallel' jobs take too much memory to store and transfer to the cluster workers. I've managed to trace it to the following: # `payload` is being written to the cluster worker. # The function FUN had been created as a closure inside my package: payload$data$args$FUN # function (l, ...) # withCallingHandlers(fun(l$x, ...), error =

Hello all, A colleague at work set me the challenge to convert some MATLAB code into R, to see which is faster. We'd seen that benchmark comparing MATLAB 6.5 to R1.90 (and others), and so I thought that I should be able to get roughly comparable speeds. The code has lots of multiplications of matrixes, transposes, and MATLAB's "repmat". I did the code conversion, and R was about

Hi all, Easy question for you (which I failed to find the answer to in the FAQ etc). I've recently been forced to switch from linux to windows (currently windows NT), and my usual habit of putting lots of "cat" statements in slow functions to get an idea of the progress rate is no longer useful. Why -- because R waits until the function is completely finished before printing the cat

Dear all, I ran into problems with the function "optim" when I tried to do an mle estimation of a simple lognormal regression. Some warning message poped up saying NANs have been produced in the optimization process. But I could not figure out which part of my code has caused this. I wonder if anybody would help. The code is in the following and the data is in the attachment. da <-

Hello, everybody: I recently encountered an example with in which the graph was placed in a way that did not leave room for a legend. Maybe you would describe it as "legend too big", I'm not sure. I found myself wishing I could force in some space after the title. Here's working example where I'd like to make room for a legend. x <- rnorm(100) hist(x, freq=F,

R-help, I 'm trying to optimize a model to data using log-likelihoods but I encounter the following error message: > l= c(49.4, 57.7,64.8,70.9,78.7,86.6,88.3,91.6,99,115) > t=3:12 > fn <- function(params, l=l, t=t) { Linf <- params[1] k <- params[2] t0 <- params[3] sigma <- params[4]

Hello, Probably a stupidly easy question, but I have done the following in order to make predictions from a fitted glm with new data: my.glm <- glm(lt96~so296[,1:17],family=binomial(link=logit)) p96 <- predict.glm(my.glm,newdata=so293[,1:17],type="response") but I always get the fitted linear predictors from the original model, ie there doesn't seem to be acknowledgement of

Full_Name: Rob Foxall Version: 2.2.0 OS: Windows XP Submission from: (NULL) (149.155.96.5) I was using multinom from nnet package, when I did something stupid -- I entered in an incorrect factor variable as response. This factor had only one level. Instead of R telling me not to be so dumb, it crashed, clicking on debug coming up with the message "An exception 'Unhandled Win32

Hello all, A really noddy question for you all: I''m trying without success to do some subhypothesis testing. Using simple anova model, with a toy dataset from a book. I have four factors A,B,C,D, and wish to test mu_C = mu_D. This is what I have tried: > contrasts(infants$group,how.many=1) <- c(0,0,1,-1) > contrasts(infants$group) [,1] A 0 B 0 C 1

Hi there, I need to run a Tobit Fixed Effects in a panel data with 4500 units for 8 years. It is a huge data set, my dependent variable is left truncated at zero, the distribution is skewed and my panel is balanced. Any suggestions on how to do that in R? I tried stuff like survreg, censReg, and tobit but none of them were satisfactory. Thanks, *Felipe Nunes* CAPES/Fulbright Fellow PhD

Hello, I am facing a problem with optimization in R from 2-3 weeks. I have some Gaussian mixtures parameters and I want to find the maximum in that *Parameters are in the form * mean1 mean2 mean3 sigma1 sigma2 sigma3 c1 c2 c3 506.8644 672.8448 829.902 61.02859 9.149168 74.84682 0.1241933 0.6329082 0.2428986 I have used optima and optimx to find the

Hi I have a package which was built using R 1.9.1 and everything worked fine. I recently upgraded to R 2.0.1 and tried to re-install my package - and I got: Error in library(mypackage) : 'mypackage' is not a valid package -- installed < 2.0.0? So I tried rebuilding it using my new version of R: R CMD BUILD --binary mypackage hhc: not found cp: cannot stat `mypackage.chm': No

Hello, I requested help a couple of weeks ago creating a dipole field in R but receieved no responses. Eventually I opted to create a 3d sinusoidal plot and concatenate this with its inverse as a means for a "next best" situation. It seems that this isn't sufficient for my needs and I'm really after creating a continuous 3d gaussian mesh with a "positive" and

Dear R users, I used to "OPTIM" to minimize the obj. function below. Even though I used the true parameter values as initial values, the results are not very good. How could I improve my results? Any suggestion will be greatly appreciated. Regards, Kathryn Lord #------------------------------------------------------------------------------------------ x = c(0.35938587,

Dear R users, I used to "OPTIM" to minimize the obj. function below. Even though I used the true parameter values as initial values, the results are not very good. How could I improve my results? Any suggestion will be greatly appreciated. Regards, Kathryn Lord #------------------------------------------------------------------------------------------ x = c(0.35938587,

Function/file names are hypothetical. Say I have written myfunction.R, which calls myfunction.c via .C("myfunction", ...). I've compiled successfully myfunction.c via R CMD SHLIB myfunction.c in the terminal. Then, in the R console: dyn.load("myfunction.so") source("myfunction.R") test <- myfunction() # works fine So everything is in order, myfunction works

Dear R-help, I have a character vector, some elements will be numeric, some not, and some even empty. E.g.: temp1 <- c("abcd"," 2 ","") I'm only interested in the numeric elements, the rest I can just throw away. It is easy enough to loop through the vector: temp <- try(eval(parse(text=temp1[1])), silent=TRUE); class(temp) # try-error temp <-

R-help, I'm just trying to find the ML (maximum likelihood) estimates of the mean and standard deviation of a set of observations: >xx=c(2.5,3.5,4,6,6.5,7.5) fn<-function(params,x=xx) { media<-params[1] st <-params[2] pdf=-sum(dnorm(log(xx),log(media),st,TRUE)) return(pdf) } optim(c(mu,stdev),fn,method="L-BFGS-B",lower=c(0.001, 0.001) ,upper = rep(Inf, 2),

Hello. I have what I know to be a simple question, but never having done anything like this it is pretty tough. I'm trying to write an R package. I have a collection of functions that I loaded into R and then used package.skeleton(). After editing everything in the resulting folder, call it NewPackage, I tried to follow along with some instructions I found for Windows users. I installed

I have some questions about 1. nomenclature, 2. recommended file locations and 3. overall procedure related to creating packages. To the extent that it matters, examples here relate to Windows XP R 2.0.1 beta. The questions are interspersed and prefaced with ***. My understanding is that there are actually 6 forms of a package that one should use in package development: 1.