similar to: Help Documentation (PR#6717)

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

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

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

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

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() <-

Avi, Yes, R (really S) was not designed for novice users but rather for experts. For better or worse it has evolved into a programming language used by tyros, and experts. Debugging tools should be easy to use, generally known, and helpful for tyro and expert. It would certainly help if R reported the line number, or the code, that generated the error. John John David Sorkin M.D., Ph.D.

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

For the question at the end, try barplot with the horiz=TRUE argument. Date: Tue, 24 Feb 2004 09:30:21 -0500 From: ivo welch <ivo.welch at yale.edu> To: <r-help at stat.math.ethz.ch> Cc: <r-help-owner at stat.math.ethz.ch>,ivo welch <ivo.welch at yale.edu> Subject: [R] Suggestions ?!?! hi chaps: * I have some suggestion, the first of which is about

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

Arguably, R was not designed or evolved for truly novice users, nor really was Python or just about all computer languages. As they evolved and became in many ways more powerful, they tended to get ever less user friendly in the way you are asking for and gotten so bloated that many features are not familiar even to expert users. Compiled languages can have ways to keep track of what LINE of code

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

understood. but, please, consider not people like me but unwary beginners and students of R. I have used R now for decades, and even I am baffled by it. Couldn't you make R code easier to debug not only for people like me (who can indeed tweak their environments) but also for novice users? On Sun, Jan 19, 2025 at 8:46?AM <luke-tierney at uiowa.edu> wrote: > > On Sun, 19 Jan

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

I am using a variant of stopifnot a lot. can I suggest that base R extends its functionality? I know how to do this for myself. this is a suggestion for beginners and students. I don't think it would break anything. first, I think it would be more useful if it had an optional character string, so users could write stopifnot( is.matrix(m), "m is not a matrix" ) this would

Dear R experts: this is probably correct behavior, but I do want to point out that it is unexpected to someone not too well versed: > test=factor("A","B","C","A") > ifelse(test=="A", as.factor("A"), test) [1] 1 2 3 1 ok, my factor was just coerced into integers, even though I have a logical vector as my condition and factors as

Dear R wizards: is there a clean way to assign to elements in a list? what I would like to do, in pseudo R+perl notation is f <- function(a,b) list(a+b,a-b) (c,d) <- f(1,2) and have c be assigned 1+2 and d be assigned 1-2. right now, I use the clunky x <- f(1,2) c <- x[[1]] d <- x[[2]] rm(x) which seems awful. is there a nicer syntax? regards, /iaw ---- Ivo Welch

dear R experts---now I have a case where I want to estimate very large regression models with many fixed effects---not just the mean type, but cross-fixed effects---years, months, locations, firms. Many millions of observations, a few thousand variables (most of these variables are interaction fixed effects). could someone please point me to packages, if any, that would help me estimate such

Dear R experts--- Has anyone written parallel versions of "by" (i.e., mcby) and "ave" (i.e. mcave) ? I did ask a question like this a year ago, and then the answer was no. for those who are googling the group for the answer to this question, in the meantime, the poor man's version of "by" is mclapply( split( ds, factor ), FUN ) I don't know the poor

every time I read the R release notes for the next release, I see many functions that I had forgotten about and many functions that I never knew existed to begin with. (who knew there were bibtex facilities in R? obviously, everyone except me.) I wonder whether there is a complete list of all R commands (incl the standard packages) somewhere, preferably each with its one-liner AND

dear R experts---I am struggling with the requirements to prepare my files for my printers. I am printing in 2/2 format, which means cyan and black for me, which they take from my color-separated pdf files. R comes into play, because it produces all the figures that are embedded in my book (pdflatex). now, TeX has no problems producing CMYK files. However, R produces RGB files (for