similar to: wishlist items ...

I am a relative neophyte to R and am faced with a problem of constructing a reduced data set from a diversity of separate sources. What operations are available in R for combining and matching attributes from separate data.frames? Thanks for any pointers/guidance! -- Russell Senior seniorr at teleport.com -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help

I would like to make readline's command history in R-0.63.1 substantially larger than it is by default (seems like around only 50 commands). How do I change the size? Thanks! -- Russell Senior seniorr at teleport.com -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send

I'd like to generate some plots like you'd see on the old "normal probability graph paper", like the first plot in: <http://www.itl.nist.gov/div898/handbook/eda/section3/normprpl.htm> except the horizontal scale would have 1%, 5%, 25%, 50%, 75%, 95%, 99%, or similar quantiles, with associated tick/grid lines. [still hunting around for a good example...] something like

I''ve been saving up a few wishlist items for zfs. Time to share. 1. A verbose (-v) option to the zfs commandline. In particular zfs sometimes takes a while to return from zfs snapshot -r tank/volumes at foo in the case where there are a great many iscsi shared volumes underneath. A little progress feedback would go a long way. In general I feel the zfs tools lack sufficient feedback

I am writing some R code that generates some figures. I am primarily developing on GNU/Linux, but will ultimately run the code on Windows in order to get WMF files I can integrate in an existing document. The win.metafile() function, of course, doesn't exist in the GNU/Linux version of R. I am contemplating writing an abstraction layer that runs the right thing, but I need to know how the

I am getting ready to load a bunch of data into R. The data is all numeric, but some of the numbers are integer codes representing non-numeric semantics. What is the best way to "fix" the data frames so that these compenents are recognized as "factors" or "ordered", as appropriate? Can I "assign" to some attribute of the data frame component, like the

I just released the Teleport gem - easy Ubuntu server setup via teleportation. Teleport sets up servers by "teleporting" to the machine and running itself there. It installs Ruby, then follows the instructions laid out in your Telfile to customize the server. https://github.com/rglabs/teleport The role/server setup is similar to Capistrano, though the syntax is slightly different. You

I am writing a little abstraction for a series of tests. For example, I am running an anova and kruskal.test on a one-factor model. That isn't a particular problem, I have an interface like: my.function <- function(model,data) { print(deparse(substitute(data))) a <- anova(lm(formula,data)) print(a) if(a$"Pr(>F)"[1] < 0.05) { pairwise.t.test(???) }

I've got a set of data that are weighted by a largish integer (ranging from about 50K to 1.5 million). I'd like to plot CDF's for this data taking into account the weighting. What do you recommend? Thanks! -- Russell Senior ``The two chiefs turned to each other. seniorr at aracnet.com Bellison uncorked a flood of horrible

I notice that devices are not hardlinked when using the --link-dest option, for instance: rsync -aH --link-dest=../bar/ foo/ baz/ When foo/zero is a device, baz/zero is not a hardlink to bar/zero. How come? $ rsync --version rsync version 2.5.6 protocol version 26 on linux 2.4.x -- Russell Senior ``I have nine fingers; you have ten.'' seniorr@aracnet.com

Suppose I have a set of binned data, counts exceeding a series of arbitrary thresholds, a total N, a minimum and maximum, those sorts of things. Is there a "standard" method for estimating arbitrary quantiles from this? My initial thought is that the counts and min/max give me solutions at various points along the empirical cdf. As the data are roughly log-normal, I thought maybe I

I am interested in making a random sample from a uniform distribution of points over the surface of the earth, using the WGS84 ellipsoid as a model for the earth. I know how to do this for a sphere, but would like to do better. I can supply random numbers, want latitude longitude pairs out. Can anyone point me at a solution? Thanks very much. -- Russell Senior ``I have nine fingers;

Given a set of data: > names(data) [1] "city" "house" "visit" "value" I am looking for a way to compute the variance components of the nested model (ie, visit 1 at house 2 at city 3 isn't related to visit 1 and house 2 at city 4), but different houses in the same city may be related, and different visits to the same house are probably

I am trying to use rsync for making snapshots, sharing hardlinks at the destination using the --link-dest option. In conjunction with this, I would like for --dry-run to report some reliable-ish number for how much space it is going to consume at the destination so that I can arrange to free such space prior the launching rsync "for effect". Right now, that isn't working: #

We have recently digitized a set of points from some scanned engineering drawings (in the form of PDFs). The digitization resulted in x,y page coordinates for each point. The scans were not aligned perfectly so there is a small rotation, and furthermore each projection (e.g. the yz-plane) on the drawing has a different offset from the page origin to the projection origin. From the dimensions

================================================= This is an automated summary of the status of the R-bugs repository. Note that this may be neither complete nor perfectly correct at any given instance: Not all bugs are reported, and some reported bugs may have been fixed, but the repository not yet updated. Some bug fixes are difficult to verify because they pertain to specific hardware or

I am generating some graphs (on GNU/Linux using R 1.5.x) for a PowerPoint presentation my boss is giving next week. He just tried cut/pasted a plot off of a PDF file I had created, but he complained that the fonts were too small and fuzzy, and that he couldn't change the background. I have been playing with png(bg=transparent), but I am not sure what appropriate height,width parameters and

I"ve got a data frame with a selection of columns I want to compute a rank-order correlation matrix from without disturbing the original data frame. foo[,c("a","b","d","f","g")] What I wanted to do, intuitively, was: > cor(rank(foo[,c("a","b","d","f","g")])) but rank in that context

Suppose you have a dataframe with two factors, but not all the factor levels appear together. For instance: stuff<- structure(list(fac1 = structure(c(2, 1, 2, 2), .Label = c("down", "up"), class = "factor"), fac2 = structure(c(1, 2, 1, 2), .Label = c("left", "right"), class = "factor"), x = c(1, 1, 2, 2), y = c(1, 2, 2, 1)),

I've been toying with the idea of using gkermit over an ssh connection. As it stands, gkermit is essentially featureless, a GPL kermit implementation that's enough to get the Free software advocated off their backs. However, since they want to continue to sell C-Kermit, it has all the `useful' features, such as scripting, but more importantly the ability to create a connection over