similar to: error building package: packaging into .tar.gz failed

I am using the example in this post: https://stat.ethz.ch/pipermail/r-help/2010-October/257204.html # create a file write.table(iris,"iris.csv",row.names=FALSE,sep=",",quote=FALSE) # this does not work # has the syntax changed or is there a mistake in my usage? # the line from the post above is: # read.csv.sql("myfile.csv, sql = "select * from file 2000,

I am trying to improve the look of an HTML table for a report (that needs to be pasted into Word). Here is an example. table2 <- structure(c(26L, 0L, 40L, 0L, 10L, 0L, 0L, 188L, 0L, 281L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 4L), .Dim = c(6L, 3L), .Dimnames = structure(list( myvar = c("Don't know", "Somewhat likely", "Somewhat unlikely", "Very

I am calculating the mean of each column grouped by the variable 'id'. I do this using aggregate, data.table, and plyr. My aggregate results do not match the other two, and I am trying to figure out what is incorrect with my syntax. Any suggestions? Thanks. Here is the data. myData <- structure(list(var1 = c(31.59, 32.21, 31.78, 31.34, 31.61, 31.61, 30.59, 30.84, 30.98, 30.79, 30.79,

I have a file in stata format, which I have read in, and I am trying to create a text file. I have exported the data using various delimiters, but I'm unable to read it back in. I originally read in the file with: library(foreign) myData <- read.dta("mydata.dta") I then exported it with write.table using comma, tab, and exclamation marks as a delimiter. When I was unable to

Hi Group, I posted this question on the ggplot list and was advised to try here also. The code below produces a plot as a png and pdf. The pdf looks great, and I cannot make the png look this way. I've tried various combinations of height, width, and dpi, but it has not worked out so far. Any suggestions to make the png look like the pdf? I received a response that the problem does not occur

I installed R 2.11.0, and I don't think I can load the doBy package now. Any suggestions? > library("doBy") Loading required package: survival Loading required package: splines Error in loadNamespace(i[[1L]], c(lib.loc, .libPaths())) : there is no package called 'Hmisc' Error: package/namespace load failed for 'doBy' > sessionInfo() R version 2.11.0

Is there an easy way to make graphs for the following data. I have pretest and posttest scores for men and women. I would like to form a 'titlted segment' plot for the data. That is, make segments joining the scores, with different types of segments for men and women. Example data: menpre <- c(43,42,26,39,60,60,46) menpost <- c(40,41,36,42,54,58,43) womenpre <-

Using this data as an example dat <- read.table(textConnection("Id myvar 12 1 12 2 12 6 34 9 34 4 34 8 65 15 65 23"), header = TRUE) closeAllConnections() how can I create another data set that does not have duplicate entries for 'Id', but the included values are randomly selected from the available ones. Thanks! Juliet

Hi, Here are three plots: library(ggplot2) data(diamonds) randind <- sample(nrow(diamonds),1000,replace=FALSE) dsmall <- diamonds[randind,] qplot(carat, data=dsmall, geom="histogram",binwidth=1) qplot(carat, data=dsmall, geom="histogram",binwidth=.1) qplot(carat, data=dsmall, geom="histogram",binwidth=.01) What are ways to put these three plots on a single

Hi, This is not an R question, but I've seen opinions given on non R topics, so I wanted to give it a try. :) How would one treat a variable that was measured once, but is known to fluctuate a lot? For example, I want to include a hormone in my regression as an explanatory variable. However, this hormone varies in its levels throughout a day. Nevertheless, its levels differ substantially

All, For my understanding, I wanted to see if I can get glmnet predictions using both the predict function and also by multiplying coefficients by the variable matrix. This is not worked out. Could anyone suggest where I am going wrong? I understand that I may not have the mean/intercept correct, but the scaling is also off, which suggests a bigger mistake. Thanks for your help. Juliet Hannah

I have downloaded a file that I don't know how to describe correctly. It contains R code and Latex, and I should be able to reproduce an analysis by running an R script in this folder. There is a line in the R script: junk <- system(paste("/usr/texbin/pdflatex ",latexFiles[i1]), intern=TRUE) that needs to be modified to run on my computer. I use WinEdt with

Dear all, I've noticed by trying to download gz files from here : https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM907811 At the bottom one can download GSM907811.CEL.gz . If I download this manually and try oligo::read.celfiles("GSM907811.CEL.gz") everything works fine. (oligo is a bioConductor package) However, if I download using download.file("

Hi Group, I have a matrix, and I would like to replace numbers less than 0 by the smallest minimum number. Below is an small matrix, and the loop I used. I would like to get suggestions on the "R way" to do this. Thanks, Juliet # example data set mymat <- structure(c(-0.503183609420937, 0.179063475173256, 0.130473004669938, -1.80825226960127, -0.794910626384209, 1.03857280868547,

Hi, I've been working with R for a couple of years, and I've been able to get most of the things done that I needed (sometimes in a roundabout way). A few experienced statisticians told me that R is best for interactive data analysis, but for large-scale computations, one needs something else. I understand that this all depends on what you are trying to accomplish, and R offers many ways

Hi Group, Here is some data. p <- runif(1000) # sample data groups <- rep(c(1,2),each=500) #conditioning variable mydata <- cbind(p,groups) n <- length(p) u <- (1:n)/(n + 1) # uniform distribution reference for qqplot logp <- -log(p,base=10) logu <- -log(u,base=10) qqplot(logp,logu) How can I make the above qqplot in lattice and/or ggplot2. The sample is uniform, and I take

With this data x <- c(0,0,1,1,2,2) y <- c(5,6,4,3,2,6) lwr <- y-1 upr <- y+1 xlab <- c("Low","Low","Med","Med","High","High") mydata <- data.frame(x,xlab,y,lwr,upr) I would like to make a dot plot and use lwr and upr as error bars. Above 0=Low. I would like there to be some space between the 5 and the 6 corresponding

Here is some sample data: mydata <- read.table(textConnection("Est Group Tri 0 0 4.639644 1 0 4.579189 2 0 4.590714 0 1 4.443696 1 1 4.588243 2 1 4.650505 0 2 4.296608 1 2 4.826036 2 2 4.765386"),header=TRUE); closeAllConnections(); I can form two plots,

Hi All, I had posted a question on a similar topic, but I think it was not focused. I am posting a modification that I think better accomplishes this. I hope this is ok, and I apologize if it is not. :) I am looping through variables and running several regressions. I have reason to believe that the data is being duplicated because I have been monitoring the memory use on unix. How can I avoid

Hi Group, Consider a data frame like this: mylabel1 <- rep(c("A","B","C"),each=3) mylabel2 <- rep(c("A","B","C"),3) corrs <- c(1,.8,.7,.8,1,.7,.7,.7,1) myData <- data.frame(mylabel1,mylabel2,corrs) myData mylabel1 mylabel2 corrs 1 A A 1.0 2 A B 0.8 3 A C 0.7 4 B