similar to: Getting host IP address?

Hi, Is it possible to have an array as the output of a custom fact? And then to pass it into a template in Puppet? I currently have a fact that looks like this: Facter.add("exports") do setcode do case Facter.hostname when (/thishost/i): [ "/local", "/local2" ] end end end & a template like this: <%

Hi, I''m trying to set up apache2 under puppet, as in this recipe: http://reductivelabs.com/trac/puppet/wiki/Recipes/DebianApache2Recipe I have a file "apache2.pp" as shown there, and then a webserver.pp file (see below). On running puppetd on the client, I get this message: err: Could not retrieve configuration: Could not find definition site in file

Hi I have a panel dataset with large number of groups and differing number of observations for each group. I want to randomly select say, 20% of the groups or 200 groups, but along with all observations from the selcted groups (with the corresponding data). I guess it is possible to generate a random sample from the groups ids and then match that with the entire dataset to have the intended

Hi I am an engineer and am running the package mgcv and specifically the command gamm (generalized additive mixed modelling), with random effects. i have a few queries: 1. When I run the command with 1000/2000 observations, it runs ok. However, I would like to see the results as in vis.gam command in the same package, with the 3-d visuals. It appears no such option is available for gamm in the

Hi, I'm trying to cross-compile R to javascript so that it can run in a web-browser. Take as long as you need to stop laughing. So, as I was saying - I want to try and get a build of R running in the browser. [If you're not familiar with it already, you might enjoy looking at emscripten.org. It's a remarkably capable tool for translating LLVM bitcode to javascript. Check out some of

Dear All, Is it possible to get confidence intervals for Harrell's concordance index or, equivalently, Somer's D using the rms package or in some other way ? I have survival data it would be the c-index in the Cox model setting Many thanks Dr Bernard North Statistical Consultant Statistical Advisory Service Advice and Courses on Research Design and Methodology Imperial College South

Dear R help My problem is very similar to the analysis detailed here. If we use the mayo dataset provided with the survivalROC package the estimate for Somer's Dxy is very negative -0.56. The Nagelkerke R2 is positive though 0.32. I know there is a difference between explained variation and predictive ability but I am surprised there is usch a difference given that even a non predictive model

Dear Sir/Madam, I am an experienced programmer that has had little exposure to R so please forgive me if I am inaccurate in places. I have an objective with which I can not find a solution. I would like to fit a GLM to binomial data that includes r number of success from n trials. The GLM that I am proposing describes P, the binomial probability of success. The link function proposed is the

Hi, I am having problems when trying to apply factor analysis in a covariance matrix, > factanal(covmat=strip1cmcd, factors=5, control=list(lower=0.0264)) Error in optim(start, FAfn, FAgr, method = "L-BFGS-B", lower = lower, : non-finite value supplied by optim In addition: Warning message: NaNs produced in: sqrt(diag(cv)) I have searched for possible solutions in

If you aleady are doing this - then thanks. But here's a feature I'd like to see. Rsync often puts a lot of load on the system because of high disk access. I'd like to see rsync become "load aware" and to slow itself down under high load levels. Seems to me that it could be something fairly easy to add to have it check the load levels and back down so as not to slow

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 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, 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

Good Morning, Is it possible to use the R program for a CFA with dichotomous data? Thank you, Kathleen Kathleen Kemp, M.A. Doctoral Clinical Psychology Student, Concentration: Forensic Psychology Drexel University Philadelphia, PA 19104 kk354@drexel.edu [[alternative HTML version deleted]]

A little off topic this morning...I'm thinking about switching out of Comast's clutches to another high-speed service. I've tried TDS DSL, but they were half the speed comast was/is. I''ve looked into Speakeasy, since I heard a few of ya talking about them. Since I had TDS, that kinda tells me I can get DSL. I live in Mount Juliet, on MT juliet road, behind the

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 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

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