similar to: how to change the history size in R

Full_Name: Russell Senior Version: 0.64.0 OS: linux-2.2.x Submission from: (NULL) (198.107.133.11) It appears that the GNU readline history size is limited to 50 entries. This is apparently occurring because R is not bothering to override the readline default value (from readline-4.0): ./history.c:59:#define DEFAULT_HISTORY_GROW_SIZE 50 It appears that it ought to be possible to override

crosstabs, merge, by, and aggregate, as discussed in section 4.2 of _Modern Applied Statistics with S-PLUS, 2ed_ would be nice. -- Russell Senior seniorr at teleport.com -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe"

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

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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 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 have compiled R under Solaris 7 (SunOS 5.7) with the readline-4.0 library linked. Command line editing appears to work, but I cannot access command history. If I execute several commands in R, then type "history()", I get the error message "Error in savehistory(file) : no history available to save". Also, previous command recall (C-p) does not seem to work. I am invoking

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

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

Hello dear R-help members, Very soon I am to give a lecture on R. And in that lecture I intend to move between: par(mfrow = c(1,1)) to par(mfrow = c(1,2)) back and forth. I anticipate this will damage the image proportions and will force me to resize the window. So far I have found it is possible to close the window and then reopen it (bigger/smaller) by using: dev.off()dev.new(width=5,