similar to: Catenating expressions in plotmath().

In the context in which I am actually working it is necessary for me to build parts of a text string to place on a plot in two separate stages. The following toy example illustrates what I am trying to do: L1 <- substitute(list(paste("Bias in ", gamma,", "))) L2 <- substitute(list(beta==b0),list(b0=300)) plot(1:10,main=L1) # Works fine. plot(1:10,main=L2) # Works fine.

Hello, I am using read.table to read files directly from a public ftp site. I have a general list of files that may or may not exist in the ftp directory, but my hope was that R would read the file if it existed and ignored it if it didn't exist and move on to the next one. However, when R arrives at a file that does not exist I get the error message "Error in file(file, "rt") :

Good Day, Included below is some code to generate data and to fit a mixed effects model to this fake data. The code works as expected when I call the function "lme" in Splus but not in R. The error message from calling lme in R is: "Error in getGroups.data.frame(dataMix, groups) : Invalid formula for groups" I installed the nlme package for R around 20 August

Hello All, My algorithm as follows; y <- c(1,1,1,0,0,1,0,1,0,0) x <- c(1,0,0,1,1,0,0,1,1,0) n <- length(x) t <- matrix(cbind(y,x), ncol=2) z = x+y for(j in 1:length(x)) { out <- vector("list", ) for(i in 1:10) { t.s <- t[sample(n,n,replace=T),] y.s <- t.s[,1] x.s <- t.s[,2] z.s <- y.s+x.s out[[i]] <- list(ff <- (z.s), finding=any (y.s==y[j])) kk

I have a data set like this in one .txt file (cols separated by !): APE!KKU!684! APE!VAL!! APE!UASU!! APE!PLA!1! APE!E!10! APE!TPVA!17122009! APE!STAP!1! GG!KK!KK! APE!KKU!684! APE!VAL!! APE!UASU!! APE!PLA!1! APE!E!10! APE!TPVA!17122009! APE!STAP!1! GG!KK!KK! APE!KKU!684! APE!VAL!! APE!UASU!! APE!PLA!1! APE!E!10! APE!TPVA!17122009! APE!STAP!1! GG!KK!KK! it contains over 14 000 000 records. Now

Dear all, I am stuck at applying loop function for creating separated plots. I have coding like below: dataset.table <- table(data.frame(var1=c(1,2,3,1,2,3,1),colour=c("a","b","c","c","a","b","b") )) kk = function(f) { ls=as.character(f) pie(dataset.table[ls,],main=ls)

This came up on r-help but indicates a bug. dnbinom(x,n,p) calls dbinom_raw(n-1,...) which returns 0 for n<1. -thomas ---------- Forwarded message ---------- Date: Thu, 08 Feb 2001 17:10:23 +0000 From: Yudi Pawitan <yudi@stat.ucc.ie> To: Mark Myatt <mark@myatt.demon.co.uk> Cc: R-Help <r-help@stat.math.ethz.ch> Subject: Re: [R] Goodness of fit to Poisson / NegBinomial

Hello, how to merge a data.frame and a matrix by one column in the data.frame and rownames of the matrix? df <- data.frame(col1=c("kk","yy","kk"),col2=c(6,4,3)) > df   col1 col2 1   kk    6 2   yy    4 3   kk    3 m<-matrix(c(3,8,56,9), nrow=2, dimnames = list(c("aa","kk"),c("col1","col2"))) > m    col1 col2 aa   

Dear all, I am dealing with the following (apparently simple problem): For some reasons I am interested in passing variables from a dataframe to a specific environment, and in fitting a standard glm: dati<-data.frame(y=rnorm(10),x1=runif(10),x2=runif(10)) KK<-new.env() for(i in 1:ncol(dati)) assign(names(dati[i]),dati[[i]],envir=KK) #Now the following two lines work correctly:

Dear folks? Is there a function to correctly find (and count) the NAs in a factor when exclude=NULL, regardless of whether their origin is in the original data or by subsequent assignment? In example number 1 below, where NAs are assigned by is.na()<-, testing the factor with is.na() finds the correct number of NAs. In example number 2, where the NAs are from the data, neither is.na(), ==NA,

I've redirected this reply from r-help to the bugs list. On 11/3/2006 8:25 AM, vito muggeo wrote: > Dear all, > I am dealing with the following (apparently simple problem): > For some reasons I am interested in passing variables from a dataframe > to a specific environment, and in fitting a standard glm: > > dati<-data.frame(y=rnorm(10),x1=runif(10),x2=runif(10)) >

Dear Sir, I am stuck with a nagging problem in using R for SVM regression. My data has 5 dimensions and 400 observations. The independent variables are : Peb, Ksub, Sub, and Xtt. The dependent variable is: Rexp. I tried using the svm.tune function as well as <_tune(svm.....), to tune the hyper parameters: gamma, epsilon and C. Since I am new to R, I am probably not using the svm.tune

Hi, I've spotted a possible memory leakage/violation in the latest R v2.1.1 patched and R v2.2.0dev on Windows XP Pro SP2 Eng. I first caught it deep down in a nested svd algorithm when subtracting a double 'c' from a integer vector 'a' where both had finite values but when assigning 'a <- a - c' would report NaNs whereas (a-c) alone would not. Different runs

Hi there, I am trying to understand how AliasAnalysis works out in LLVM. I used the following simple test-case (test4.c): -- void test() { int *jj, *kk; int aa = 100; jj = &aa; *jj = 300; } int main() { test(); return 0; } -- Then I did "llvm-gcc -emit-llvm -c -o test4.bc test4.c" to get bc. I tried the following 2 ways to get what I expect to get as

Hello all: I don't know what I'm doing bad, but --link-dest does not work for me: I have three directories, the original one, the first copy and the second copy I want to populate: $ ls -li total 12 1761433 drwxr-xr-x 2 envite envite 4096 dic 10 14:04 copy1 1761434 drwxr-xr-x 2 envite envite 4096 dic 11 01:18 copy2 1761432 drwxr-xr-x 2 envite envite 4096 dic 10 14:04 origin $ ls -li *

Hi, When validating users on my Linux system against an ActiveDirectory, the Windows event log are filled with messages like these (Windows Event ID 675): Pre-authentication failed: User Name: linux$ User ID: KK\linux$ Service Name: krbtgt/KK.LOCAL Pre-Authentication Type: 0x0 Failure Code: 0x19 Client

Hi Eli, thanks for the answers helping out. I tried to understand further - got another example: void test() { int *jj, *kk; int aa = 100; jj = &aa; *jj = 300; kk = jj; *kk = 400; } int main() { test(); return 0; } bc looks like the following (only test() part) define void @test() nounwind { entry: %aa = alloca i32 ; <i32*> [#uses=2] %kk =

Dear Sir/Madam, I am stuck with a nagging problem in using R for SVM regression. My data has 5 dimensions and 400 observations. The independent variables are : Peb, Ksub, Sub, and Xtt. The dependent variable is: Rexp. I tried using the svm.tune function to tune the hyper parameters: gamma, epsilon and C. I am getting the following error message: Error in predict.svm(ret, xhold,

Hi, r-gurus: I happened to have a question in my work: I have a dataset, which has only one dimention, like 0.99037297527605 0.991179836732708 0.995635340631367 0.997186769599305 0.991632565640424 0.984047197106486 0.99225943762649 1.00555642128421 0.993725402926564 .... the data is saved in a file called f392.txt. I used the following codes to play around :)

Hi all, I have a problem with retreaving column from a data.frame that is I have a data.frame named "temp" in that dataframe some column are there whose names are "IDENTIFIER" "UNIQUEID" "TRIALGROUPSID" "GRPNUMBER" "GRPDESC" "SEXDID" "STDID" "STUDYTYPE" "SDID"