similar to: Help Documentation

Ivo, Let me address your points in reverse order: 1. There is a `wishlist' category for bug reports, which I guess you've overlooked. 2. There is also a `Contributed Documentation' section on the R web site, which you can submit your contribution. As well, there are a few introductory level documents there already that you might be interested. 3. I must repectfully disagree about

I think many people share your view and are aghast at the reception that some well-intentioned posts receive. There have been past discussions on this and many people feel the way you and I do. Just to head off another round, let me acknowledge that there appears to be multiple viewpoints and although hard to believe by myself, there actually is a contingent that views what I see as

Dear all,=20 without taking sides here, I see two major advantage of keeping the redundancy in any documentation minimal. First, it makes the maintanance of the documentation as simple as possible. This in turn, minimizes the risk for getting inconsistent documentation in new updates. Otherwise, someone has to have a really good overview and know where to update when, say, one default argument is

hi henrik (all): A better solution would be to have levels: set.help(level="beginner"), which then provides expanded explanations. However, I do not think this is necessary: For the most part, the online R docs are great. It is not more detailed explanations that beginners crave. My primary wishes arise as I stumble onto a need, and then wish for a few more examples of different

ladies and gents: I have posted a couple of simple questions recently. As often happens to novices, the information was there somewhere, even in front of my eyes, and I just did not see it. I looked in docs that seemed to me to be the right place for this particular information, but did not find it. There is no question: mea culpa, and everything is documented somewhere in R. (Worst

Full_Name: ivo welch Version: 1.8.1 OS: linux Submission from: (NULL) (130.132.33.212) please define aliases for the 5 essential data set operations delete row insert row delete column insert column rename column these are too difficult for novices as-is now, and the cost for doing this for you would be very low. if need be, define hints only, such as dataset.del.row() <-

On 28 Mar 2004 at 16:52, ivo welch wrote: > > ladies and gents: > > I have posted a couple of simple questions recently. As often happens . . . > I was told by Brian to stop sending such suggestions, in order not to > clutter the R bug report list. OK, I can save my time; I just wanted He told you stop sending them to R-bugs! When you get a little more experience, send them

Why does stop("we are done") print "Error in eval.with.vis(expr, envir, enclos) :" ? It would seem to me that a plain stop() is not an error, and that it would make more sense to have an error() function that is different from a stop(). Is there a rationale here that I am missing? sincerely, /iaw

dear R wizards: an operation I execute often is the deletion of all observations (in a matrix or data set) that have at least one NA. (I now need this operation for kde2d, because its internal quantile call complains; could this be considered a buglet?) usually, my data sets are small enough for speed not to matter, and there I do not care whether my method is pretty inefficient (ok, I

Full_Name: ivo welch Version: any OS: linux Submission from: (NULL) (130.132.33.212) hi: in "?stop", in "See Also", please add "quit()" as a mention. Similarly, I would create a help for ?exit, which simply states that "you are probably looking for quit() or stop()". regards, /ivo

dear R wizards: X is factor with 20,000*20=800,000 observations of 20,000 factors. I.e., each factor has 20 observations. y is 800,000 normally distributed data points. I want to see how much R^2 the X factors can provide. Easy, right? > lm ( y ~ X) and > aov( y ~ X) Error: cannot allocate vector of size 3125000 Kb is this computationally infeasible? (I am not an expert, but

Dear R developers: R is supposed to be slow for iterative calculations. actually, it isn't. matrix operations are fast. it is data frame operations that are slow. R <- 1000 C <- 1000 example <- function(m) { cat("rows: "); cat(system.time( for (r in 1:R) m[r,20] <- sqrt(abs(m[r,20])) + rnorm(1) ), "\n") cat("columns: "); cat(system.time(for (c

hi: would it be useful to build into R an optional mechanism that typechecks arguments? for example, sum.across <- function ( inpmatrix : matrixtype( dim[1]>1, dim[2]>3 ) ) : vector { } # this would define a sum.across function that can take matrices or data sets, but not vectors, # and which indicates that it will return a vector. xsum <- sum.across( 1:10

I ran into an interesting oddity of R, if (0) { print(1); } else { print(2); } is a syntax error, while if (0) { print(1); } else { print(2); } or if (0) { print(1); } else { print(2); } is not. I presume it has to do with the duality of the newline functioning as an end of command (;) character, though it still seems a bit odd, and it took me a while to figure out

hi: I searched the last 2 hours for a way to enter a data frame directly in my program. (I know how to read from a file.) that is, I would like to say something like d <- this.is.a.data.frame( c("obs1name", 0.2, 0.3), c("obs2name", 0.4, 1.0), c("obs3name", 0.6, 2.0) ,

Full_Name: ivo welch Version: current OS: linux Submission from: (NULL) (130.132.33.212) * In the ?subset page, please add subset( dataframe, select= c(-column1,-column2) ) returns a dara frame that is without columns 1 and 2 . * Also, in ?lm, it would be nice to add a few more words about how to get a residuals vector of the same length as the variable vectors, even if there

dear R experts: I want to define a function the calculates the black-scholes value. it takes 5 named parameters, BS <- function(S,K,dt,rf,sigma) {} . let's presume I want to be able to call this not only with my 5 numeric vectors BS( sigma=0.3, S=100, K=100, dt=1, rf=0.1 ) and BS( 100, 100, 1, 0.1, 0.3), but also with a data frame that contains the variables alll in a neat data frame

dear wizards: FYI: gentoo is a linux meta distribution, which compiles all packages. Once running, gentoo is stable on most applications. (it has some problems with system tools, such as grub.) the compiler is gcc 3.3.3. I do not expect anyone to track down for me why R fails on the gentoo amd64+gcc3.3.3 system, but I thought that it would be good to put it on the record to save

dear wizards: FYI: gentoo is a linux meta distribution, which compiles all packages. Once running, gentoo is stable on most applications. (it has some problems with system tools, such as grub.) the compiler is gcc 3.3.3. I do not expect anyone to track down for me why R fails on the gentoo amd64+gcc3.3.3 system, but I thought that it would be good to put it on the record to save

hi: apologies for taking up everyone's time. my problem is probably documented somewhere, but I again cannot find it. (which reminds me: I cannot find a search engine that allows me to search the archives of this very useful mailing list.) * it seems that lines(lowess()) fails to plot certain line segments. (and, what does it do at the x-min and x-max of a data set?) Rather than