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Dear R experts, please excuse me for writing to the mailing list without subscribing. I have a somewhat urgent problem that relates to R. I have to process large amounts of data with R - I'm in an international collaboration and the data processing protocol is fixed, that is a specific set of R commands has to be used. I wrote a perl program that manages creation of data subsets from my

Dear R-help, I'd like ask for your opinion on choosing the "right" strategy for a particular dataset. We conducted 24-hour electric field measurements on 90 subjects. They are grouped by job (2 categories) and location (3 categories). There are four exposure metrics assigned to each subject. An excerpt from the data: n job location M OA UE all 0 job1 dist_200 0.297 0.072 0.171

Dear R-help list, I'd like to create visualize the clustering of a dataset with a dendrogram. I'm using the following script: data = read.table("data.csv", header=T, sep=";") require(cluster) res = as.dendrogram(agnes(data)) chlab <- function(n) { if(is.leaf(n)) { att <- attributes(n) labx <- data$category1[att$label] lab_color <- ifelse(labx ==

Reposting from R-help: Dear R experts, please excuse me for writing to the mailing list without subscribing. I have a somewhat urgent problem that relates to R. I have to process large amounts of data with R - I'm in an international collaboration and the data processing protocol is fixed, that is a specific set of R commands has to be used. I wrote a perl program that manages creation of