similar to: how to break the loop using sapply?

Dear expeRts, ?? I am fammilar with matlab , i want to call some r codes from it , what can i refer? ?I tried R.matlab. But it seems can't work well. so, do you have any other suggestions? -- PO SU mail: desolator88 at 163.com Majored in Statistics from SJTU

Dear Rdevelers, ? ? ?The following struct is in the Rinternals.h. I want to know ?the meanings of labels or names like "gp,mark,obj,named,trace....." . TKS! struct sxpinfo_struct { ? ? SEXPTYPE type ? ? ?: ?5;/* ==> (FUNSXP == 99) %% 2^5 == 3 == CLOSXP ? ? * -> warning: `type' is narrower than values ? ? * ? ? ? ? ? ? ?of its type ? ? * when SEXPTYPE was an enum

Dear expeRts, ??? When i use the following codes: ??? pdf(file="1.pdf",width=15) ? ? plot(1:3,main="??") ??? dev.off() #There were 12 warnings (use warnings() to see them) ? I find that "??" can't show correctly in pdf file, but? i just ?plot(1:3,main="??") to R plot viewer, it's ok . ? Is there anyone happen to know the solution? BTW, i explore the

Dear expeRts, ?? I find the newest Rstudio Desktop v0.98.1049 ?for windows is not newest, after i installed, it was a old version. -- PO SU mail: desolator88 at 163.com Majored in Statistics from SJTU

The solution post is here: http://lists.r-forge.r-project.org/pipermail/rcpp-devel/2012-November/004771.html In the paragraph: I did need however to install Rcpp and RInside from source, and with the same compiler used to compile qtdensity (otherwise I would get additional linker errors). As I had trouble getting the (Cygwin-based) g++ shipped with Rtools to work with Qt, I used instead the

Hi I like to use "axis.POSIXct" to plot days from 2006 till 2008. But I only have datas for the summer months. Is it possible to get two axis breaks, to have not so long distances without points? thx Christof

Dear All   I have the following data (somewhat simplyfied):   TINF <-1 a <-c(500,750,1000,1250,1500,1750,2000) b <-c(8,12,18,24,36,48,60,72,96)   following function:   infcprodessa <-function (D, tin, tau, ts)   (D * (1 - exp(-0.048 * tin))/(tin * (0.048*79) * (1 - exp(-0.048 * tau)))) * exp(-0.048 * (ts - tin)) z <-sapply(1:1, function(n) infcprodessa(1000,TINF,12,12-TINF))   is

Are they the same with .RData being the newer format?? Thanks, ...Tao

Dear all, I have an R script that uses Rcpp, and I have been trying to parallelize it using mclapply (I tried with the multicore and the parallel library) Sometimes (not always, interestingly), the CPU use for each core drops, usually so that the total over all cores reaches 100%, i.e., as fast as if using just one single core fully. I tried my code directly from within emacs, and also using a

Hi, I'm trying to user lmer function from lmerTest package because, if I understood correectly, it allows to make better inference than lmer method from lme4 package. However, whatever I do I keep getting this error: Error in lme4::lFormula(formula = mark ~ ssCount + sTime+ : rank of X = 1660 < ncol(X) = 1895 any ideas what could be a problem? thanks, Srecko [[alternative HTML

Dear all, I am working with a list of objects each of which contains two POSIXct objects (say, $Start and $End) and a number of different data in addition to that. Now an easy way to extract Start times of all object could be sapply(x, "[", "Start") but this converts them all to numeric, and so does sapply(x, "[[", "Start"). lapply preserves the class but

Hello r-help, I've been banging my head against the computer in an attempt to learn how to divide my matrix into segments by rows. I want to be able to return each segment as a newly named object. I've tried looking at the apply functions and creating a for loop but brain no work. Here's the basic starting objects that I believe would be needed to separate the matrix. mat <-

x <- c( "a1", "a10", "a2" ) y <- c( "b10", "b2", "a12", "ca1" ) DF <- expand.grid( x = x, y = y ) # randomize set.seed( 42 ) DF <- DF[ sample( nrow( DF ) ), ] # missing from gtools mixedrank <- function( x ) { seq.int( length( x ) )[ gtools::mixedorder(x) ] } o <- do.call( order, lapply( DF, mixedrank ) )

Friends I clearly donot understand how sapply and vapply work. What I have is a function that returns a matrix with an indeterminate number of rows (some times zero) but a constant number of columns. I cannot reliably use an apply function to assemble the matrices into a matrix. I am not sure it is possible. I can demonstrate the core of my confusion with this simple code. A.f <-

Dear list, perusing the GMane archive shows that the issue with XML 3.4.x still bugs odfWeave users. I just checked that the newer XML 3.4.2 version still give the same problem. Using it to weave a bit of documentation written with LibreOffice 3.3.3 (current in Debian testing) leads me to a 192 Kb, 590 pages document, whereas reinstalling XML 3.2.0 gives me a 4 pages, 24Kb file (not

# trying to do a copy and a transform within a data frame, but getting the "arguments imply differing number of rows" error, and I'm not sure why a=c(1,2,3) b=c(2,3,4) c=c("Yes","No","Yes") d=c("No","Yes","No") df=data.frame(a,b,c,d) # the following works fine! df = transform(df, new=sapply(df[,c(1,2)], FUN = function(x)

Dear R users, I am running simulations (1000), and in my simulation I am looking at specific sums. For example, if the sum is >=4 then count this, if say <3, then don't count, if the sum=3, then generate a random number from uniform distribution, if this number is say less than 0.5, then count this sum, if greater than 0.5, then don't count. I am having trouble with introducing this

Hi all: My OS is 32bit winxp,but I wanna install 64bit R2.14.1. >From the following website,it says "You can also go back and add 64-bit components to a 32-bit install, or vice versa" http://cran.r-project.org/bin/windows/rw-FAQ.html#Can-both-32_002d-and-64_002dbit-R-be-installed-on-the-same-machine_003f Does it mean that I can install and run 64bit R2.14.1 under 32bit

In the following data.frame there are 6 columns, but 7 are written to the CSV file. install.packages("pmlr") library(pmlr) data(enzymes) write.table(enzymes, sep=",", eol="\n",file="albert.csv")

Hi, I am trying to normalize some data. First I fitted a principal curve (using the LCPM package), but now I would like to apply a transformation so that the curve becomes a "straight diagonal line" on the plot. The data used to fit the curve would then be normalized by applying the same transformation to it. A simple solution could be to apply translations only (e.g., as done after a