similar to: RODBC and Excel: Wrong Data Type Assumed on Import

I need to process some datasets where the configuration information was stored in .INI-like files, i.e., text files with sections like this: [Section1] var1=value1 var2=value2 [Section2] A=value3 B=value4 ... >From Google and other searches I haven't found any package, or function within a package, that reads .INI files into an R list, or other data structure. Any suggestions, or

I've always been frustrated that R never puts a label on the column name for a column of row names. This is usually the "key" in a database table, and it sure would be nice to carry a "key" name along with the data instead of the field being blank. So, why is it a good idea for it to be blank? ?write.csv says this: CSV files By default there is no column

bonjour, i'm a mathematic teacher and i have a question for R-developers : is it possible to have (in the future) a boxplot with whiskers from the first decile to the ninth decile, as usual in secondary french schools... by example : boxplot(serie,range=-1) for french boxplot ? cordialement, jean-pierre lyc?e jean zay orl?ans, france http://mathazay.free.fr/spip/

In 2004 there was this R-Help posting from Jan 2004: http://finzi.psych.upenn.edu/R/Rhelp02a/archive/33097.html R equivalent of Splus peaks() function? The peaks function there has worked well for me on a couple of projects, but some code using "peaks" failed today, which had worked fine in the past. I was looking for a peak in a test case that was a sine curve over one

Does R have a dir.choose function? I can use file.choose like this as a kludge to get something like a dir.choose, but a real dir.choose would be better: cat("Select one of files in directory to process:\n") filename <- gsub("\\\\", "/", file.choose()) basepath <- dirname(filename) Windows provides a lower-level SHBrowseForFolder function to create such

The Partek package (www.partek.com) allows only two selections for Multiple Test Correction: Bonferroni and Dunn-Sidak. Can anyone suggest why Partek implemented Dunn-Sidak and not the other methods that R has? Is there any particular advantage to the Dunn-Sidak method? R knows about these methods (in R 2.1.1): > p.adjust.methods [1] "holm" "hochberg" "hommel"

# This works fine: > a <- 1 > b <- 2 > c <- 3 > E <- expression(a * exp(b*X) + c) > X <- c(0.5, 1.0, 2.0) > eval(E) [1] 5.718282 10.389056 57.598150 > D(E, "b") a * (exp(b * X) * X) > eval(D(E, "b")) [1] 1.359141 7.389056 109.196300 # But if (a,b,c) are replaced with (A[1], A[2], A[3]), how can I get a derivative

Hi all. I'd like know what is the format file saved by Leica Microsystems TCS SP2-AOBS equipped with a SP2-FCS2 Leica Microsystems workstation its datas. Cause it save in *.fcs extention file but ins't flow cytometry standart format file... Tahnks Horacio.

Hi R, I have an excel file in which the third column is "date" and others are "character" and "numeric". Number of columns are 12 If I use this to read the file in R: x = read.xls("D:\\file.xls") The problem is that my date column is read in julian dates. So I am using: x = read.xls("D:\\file.xls",

Hi all, excuse me by this elementary question. I wish to know if a package in language R exists to analyze FCS (Fluorescence Correlation Spectroscopy) datas. And, if it possible, in addition can read the archives in raw format generated by the ConfoCor2 program. Thanks Horacio. **************************************************************************** Dr. Horacio Castellini

I want to get some "simple" logic regression examples to work before exploring a hard problem. I can get results, but I'm having some problems using "cat" to save the logic regression equation to a disk file. Consider this: # Simple Logic Regression Example # efg, 23 Feb 2005 library(LogicReg) # Create simulated data with known logic equation: # "noise"

R version 2.5.1 (2007-06-27) I' running some simple R jobs via the Sun Grid Engine on our Linux cluster in preparation for some bigger ones. I checked R's capabilities on the cluster nodes (after failing to create a png file) and am getting the following warning message: [Run on a cluster node using qrsh:] > capabilities() jpeg png tcltk X11 http/ftp sockets

Hi, Does anyone know the name of the package that includes a function for computing the lomb periodogram on irregular spaced ts data? I saw the package once ~ 1 month ago but cannot find it now ... , Rich

Dear time-series specialist: I've got some time series representing measurements from a physical process, like atomic decay data. These time series look almost random, but should hopefully be distinguishable as they were taken under different conditions. I am looking for statistical approaches that are sensitive enough to discriminate between such series of measurements. Preferably, there

Hi list, I will help an person that will use some graphics of R in internet. But this pearson want to specify the colours. This person want me to create an pallete of colours like that: Name of color - Code - Colour White - 0xFFFFFF - color white (like an box with this color) I know that is possible with R, but i don't know how. Thanks for the advance. Atenciosamente, Leandro Lins

"white" is supposed to be the default background for BMPs (according to ?bmp) but it doesn't work > bmp("test.bmp", bg="white") > plot(0) > dev.off() # results in grey background # This seems to be a good enough workaround for now. > bmp("test.bmp") > par(bg="white") > plot(0) > dev.off() # background is white

Consider: > x <- matrix(1:6, 2,3) > rownames(x) <- c("ID1", "ID2") > colnames(x) <- c("Attr1", "Attr2", "Attr3") > x Attr1 Attr2 Attr3 ID1 1 3 5 ID2 2 4 6 > write.csv(x,file="x.csv") "","Attr1","Attr2","Attr3" "ID1",1,3,5

  I have timeseries data for some factors, and some missing values are there in those factors, I want impute those missing values without disturbing the distribution of that factor, and maintaining the correlation with other factors. Pl. suggest me some imputation methods. I tried some functions in R like aregImpute, transcan. After the imputation I am unable to retrive the data with imputed

I'm having problems getting nls to agree that convergence has occurred in a toy problem. nls.out never gets defined when there is an error in nls. Reaching the maximum number of iterations is alway an error, so nls.out never gets defined when the maximum number of iterations is reched. >From ?nls.control: tol: A positive numeric value specifying the tolerance level for the

Dear all, May I suggest to add an example in the help page of the colors() function ? The following code could be useful to easily choose any color from colors() : ## Millot G. (2011), p.71. ## Figure displaying all the 657 built-in color names of colors(). palette(colors()) tempo<-NULL for(i in 14:1){tempo<-c(tempo, rep(i,50))} windows(width=10) # replace by quartz(width=10) for MacOS and