search for: macaladi

Hi, I have a data set that I'd like to run logistic regressions on, using ddply to speed up the computation of many models with different combinations of variables. I would like to run regressions on every unique two-variable combination in a portion of my data set, but I can't quite figure out how to do using ddply. The data set looks like this, with "status" as

Hi, I would like to plot a bunch of tree ring width data (time series) using ggplots, but I'm having trouble figuring out how to do it. My data is in a data.frame, with years as rownames and a distinct tree ring series in each column. So, something like this: rwl<-matrix(rnorm(800), nrow = 100) colnames(rwl) <- paste('V', 1:8, sep = '')

Hi, I have a 5-paneled figure that i made using the facet function in qplot (ggplot). I've managed to arrange the panels into two rows/ three columns, but for the sake of easy visual comparisons between panels in my particular dataset, I want to have the two plots on the bottom align on the right hand side of the figure instead of the left. Here's an example: m <-

Hi, I've tried to figure this out using Intro to R and help(), to no avail - I am new at this. I'm trying to write a script that will read multiple files from a directory and then merge them into a single new data frame. The original data are in a tree-ring specific format, and so I've first used a function (read.rwl) from the dplR package to read each file, translate each into a

I have a data.frame with ~250 observations (rows) in each of ~50 categories (columns). I would like to perform t.tests on subsets of observations within each column, with the subsets according to index vectors contained in other columns of the data.frame. My data.frame looks something like this: x<-data.frame(matrix(rnorm(200,mean=5,sd=.5),nrow=20)) colnames(x)<-c("site",

Thank you for reading. I am trying to get sphericity values, and I understood I need to use mlm, but how do I implement a nested within subject design in mlm? I already read the R newsletter, fox chapter appendix, EZanova, and whatever I could find online. My original ANOVA anova(aov(resp ~ sucrose*citral, random =~1 | subject, data = p12bl, subset = exps==1)) Or anova(aov(resp ~