similar to: Full enumeration, how can this be vectorized

Greetings Friends, I would be grateful if you can help me undestand how to make my R code more efficiently. I have read in R intoductory tutorial that a for loop is not used so ofter (and is not maybe not that efficient) compared to other languages. So I am trying to build understanding how to get the equivalent of a for loop using more R-oriented thinking. If I got it right one way to do that

Dear all, I have a 100 iteration loop. Within each loop, there are some calls to rpart() like: ctl <- rpart.control(maxcompete=0, maxsurrogate=0, maxdepth=10) temp <- rpart(y~., x, w=wt, method="class", parms=list(split="gini"), control=ctl) res <- log(predict.rpart(temp, type="prob")) newres <- log(predict.rpart(temp, newdata=newx,

Hi, I pulled compiz from GIT yesterday to see if I could get proper multi-head support. I think the current status is great, but I have one little suggestion to make. The current behavior is that we have two viewpoints of the "cube" (it's more like a body with eight side planes now). If it's rotated one step we skip one of the planes. Rotating four times is enough to go round

I am using R 2.5.0 on windows XP and trying to fit copula. I see the following code works for some users, however my code crashes on the chol. Any suggestions? > mycop <- tCopula(param=0.5, dim=8, dispstr="ex", df=5) > x <- rcopula(mycop, 1000) > myfit <- fitCopula(x, mycop, c(0.6, 10), optim.control=list(trace=1), method="Nelder-Mead")

Merry Xmas to all, I am writing a function and curiously this runs sometimes on one data set and fails on another and i cannot figure out why. Any help much appreciated. If i run the code below with data <- iris[ ,1:4] The code runs fine, but if i run on a large dataset i get the following error (showing data structures as matrix is large) > str(cluster.data) num [1:9985, 1:811] 0 0 0 0

Dear All, Need some help as I was trying to follow the guide below. https://wiki.samba.org/index.php/Samba4/HOWTO/Join_a_domain_as_a_DC Until the steps of ldbsearch -H /usr/local/samba/private/sam.ldb '(invocationid=*)' --cross-ncs objectguid and my ldbsearch reply with such a result. ldb: unable to dlopen /usr/lib64/samba/ldb/acl.so : /usr/lib64/ldb/libreplace.so: version

Hi,all: I met a problem of nls. My data: x y 60 0.8 80 6.5 100 20.5 120 45.9 I want to fit exp curve of data. My code: > nls(y ~ exp(a + b*x)+d,start=list(a=0,b=0,d=1)) Error in nlsModel(formula, mf, start, wts) : singular gradient matrix at initial parameter estimates I can't find out the reason for the error. Any suggesions are welcome. Many thanks. [[alternative HTML

Hello everybody When one is working with complex matrices, "transpose" very nearly always means *Hermitian* transpose, that is, A[i,j] <- Conj(A[j,i]). One often writes A^* for the Hermitian transpose. I have only once seen a "real-life" case where transposition does not occur simultaneously with complex conjugation. And I'm not 100% sure that that wasn't a

I have to admit I don't fully understand how MatLab's step() function works, but I'm learning that part. Can someone point me to equivalent&related functions in R? thanks Carl

Hi, How to add values to an array at any position. Asking because of the following: e.g. y<-c(0.1,NaN,0.2,NaN) #or data frame x<-na.omit(y) take some columns from x and do some computation with functions which do not allow NaN 's. After the computing add NaN's at positions stored in attr(x,"na.action") of the result vector. /E -- Dipl. bio-chem. Witold Eryk

Hello everyone, I have a dataset which includes the first three variables from the demo data below (year, id and var). I need to create the new variable ans as follows If var=1, then for each year (where var=1), i need to create a new dummy ans which takes the value of 1 for all corresponding id's where an instance of one was recorded. Sample data with the output is shown below. year

Dears useRs, I am using the mle function but this gives me the follow erros that I don't understand. Perhaps there is someone that can help me. thank you for you atention. Bernardo. > erizo <- read.csv("Datos_Stokes_1.csv", header = TRUE) > head(erizo) EDAD TALLA 1 0 7.7 2 1 14.5 3 1 16.9 4 1 13.2 5 1 24.4 6 1 22.5 > TAN <-

Dear R community. I am using the identify() function to identify outliers in my dataset. This is the code I am using: #################################################################### # Function to allow identifying points in the QQ plot (by mouseclicking) qqInteractive <- function(..., IDENTIFY = TRUE) { qqplot(...) -> X abline(a=0,b=1) if(IDENTIFY) return(identify(X))

I've finally gotten around to playing with the advanced menu, though the complex example is definitely still beyond me. I'm trying to figure out a few basics from it, such as the tab key for line editing (don't know what I've done wrong here since it seems like I copied that part right) and the timeout. It looks to me like the only ontimeout implemented so far is an option to not

I have a dataframe ("mydf") that contains "differences of means". I wish to test whether these differences are significantly different from zero. Below, I calculate the t-statistic for each column. What is a "good" method to calculate/look-up the p-value for each column? mydf=data.frame(a=c(1,-22,3,-4),b=c(5,-6,-7,9)) mymean=mean(mydf) mysd=sd(mydf)

Dear List, I am having problems converting a file with fractional seconds to class POSIXct. I have set my options to include digits.secs and my format to just time, but my output is the current date with my time lacking the fractions of a second. For example: options(digits.secs=3) t<-c("06:00:00.100","06:00:01.231") myt<-as.POSIXct(t,format="%H:%M:%S")

Hello, I'm trying to create my own C code for use within R. While optimizing the code I've noticed that even while only using pointers to get my data to C the time needed still depends on data (vector) size. To test this, I've created an empty C function to which I've send vectors containing various sizes of elements. The time needed for each call is measured and plotted. I would

Dear R-devel, [I'm not sure if this is appropriate for R-devel. If not, I'm more than happy to move it to R-help.] As those of you who saw my post on R-help know, I've been trying to build R-patched on a dual Opteron box running Scyld Beowulf, using the PGI 6.1 compilers. The build went fine, but I couldn't get it to pass make check-all. Jennifer Lai, who reported success with

I am using rsync version 2.6.9 protocol version 29 on a Fedora 7 system to backup files to a network drive. rsync is getting I/O errors when copying maildir files (I'm not sure if the error is happening with other files but these are the only ones I have found so far). I have done some tests on one particular directory, "cp -R" succeeds but "rsync -r" fails:- home#

WARNING: This is not compatible with the previous lz4 patchset. If you''re using experimental compression that isn''t in mainline kernels, be prepared to backup and restore or decompress before upgrading, and have backups in case it eats data (which appears not to be a problem any more, but has been during development). These patches add lz4 and lz4hc compression