similar to: multiple plots and postscript()

Hi everyone This must be a FAQ but I can't find it anywhere... I want a postscript image of a contour() plot, with axes of equal length. Try R> postscript(file="~/f.ps") R> contour(matrix(rnorm(100),10,10)) R> dev.off() This isn't what I want: the plotting region is, as documented, quarter of an inch shy of the paper edge and the axes appear to be different lengths.

Hello List How do I turn R> simple.example.alphabetic [,1] [,2] [,3] [1,] "a" "b" "c" [2,] "d" "e" "f" [3,] "g" "h" "i" into R> simple.example.numeric [,1] [,2] [,3] [1,] 1 2 3 [2,] 4 5 6 [3,] 7 8 9 [ie "a" becomes 1, ..., "z"

Hello everybody I have a generic problem which the following toy function illustrates: f <- function(n) { if(abs(n) < pi) { return(TRUE) } else { return(FALSE) } } I want it to return TRUE if abs(n)<pi and FALSE otherwise. f() is fine as far as it goes, but does not deal well with NA or NaN or NULL (I want these to signal some problem with the

Hello everyone. If I do f <- function(n){max(rnorm(n))} plot(sapply(rep(5000,4000),f)) #[this takes my PC about 30 seconds] then I get something quite unexpected: gaps in the distribution. For me, the most noticable one is at about 3.6. Do others get this? Is it an optical illusion? It can't be right, can it? Or maybe I just don't understand the good ol' Gaussian very

Hello ALL: How do I get R to list all possible orderings of 2 x's and 3 y's? It should look like this (which rows appear first is unimportant): x x y y y x y x y y x y y x y x y y y x y x x y y y x y x y y x y y x y y x x y y y x y x y y y x x Thanks, ANDREW

Hello list (thanks for all the help on my data.frame() question, especially to Professor R for a working script...I was pleased to see the solution wasn't obvious!) Anyway, now I'm trying to run R in batch mode, but I'm getting extra output, which I don't want (RedHat 8.3, R-1.7.0): r:~% cat test.R options(echo=FALSE) write(rnorm(4),"") r:~% R CMD BATCH --vanilla

Hi everyone check this out [R-1.7.0]: R> f1 <- function(x){x^2} R> f1 -> f2 R> f2(4) [1] 16 R> R> function(x){x^2} -> f3 function(x){x^2} -> f3 R> f3(4) Error: couldn't find function "f3" Why does right assignment "->" work in the first but not the second case? Can anyone else reproduce this? -- Robin Hankin, Lecturer, School of

Hello everybody. Does anyone else find the last test in the following sequence odd? Can anyone else reproduce it or is it just me? > binom.test(100,200,0.13)$p.value [1] 2.357325e-36 > binom.test(100,200,0.013)$p.value [1] 6.146546e-131 > binom.test(100,200,0.0013)$p.value [1] 1.973702e-230 > binom.test(100,200,0.00013)$p.value [1] 0.9743334 (R 1.5.1, Linux RedHat 7.1) --

Hi everyone another documented feature that was a bit unexpected for me: R> x <- 19 R> f <- function(t){t+x} R> f(100) [1] 119 --as expected: x is visible from within f() ..but... R> g <- function(a){x <- 1e99 ; return(f(a))} R> g(4) [1] 23 --the "x" that is visible from within g() is just 19, which is not the one I expected it to find. R> rm(x)

Hi everyone thanks for the replies. The issue was NOT a font problem; I deliberately chose ll1 and l11 as examples of easily confused variable names (evidently these were too easily confused ;-). The code snippet was written as intended, and increment() contained a deliberate, highlighted, bug. I was asking for guidance on avoiding/finding this sort of coding error. That was why I wrote

Hello everybody. I have a question that has stumped me and the usual "apply" tricks don't seem to work. I run a course where each student's performance is marked by one or more assessors. I have a data frame containing students' names, assessors' names and their marks, arranged as follows: ID student assessor Q1A Q1B Q1C Q2A Q2B Q3 1 2152833

Hola! Sorry for going off-topic, but here are something I found on the web yesterday - an explanation of statistics in poetic form: First, you see your data for what they seem to be Then, you ask them for the truth - are you what you seem to me? You see with broad expanse you ask with narrowed power you see and ask and see and ask and see... and ask

Dear R People: Does anyone have any code for Fractals, chaos, or anything like that, please? This is strictly for demo purposes...decorative only. This is R version 1.5.1 for Windows. Thank you in advance! Have a great weekend! Sincerely, Erin Hodgess Associate Professor Department of Computer and Mathematical Sciences University of Houston - Downtown 1 Main Street Houston, TX 77002

Dear R community A few weeks ago, I uploaded a small text file called R-and-octave.txt to the contributed docs section of CRAN. This file details octave/matlab commands and their (near) equivalents in R (Matlab is a widely-used high-level graphics/mathematics tool and octave a free clone). Someone has just pointed out to me that I never announced its existence to anyone, hence this email (I

Hello R experten I have just written a little function to calculate all pairwise combinations of two vector arguments: > pair(c(1,2,3),c(7,8)) [,1] [,2] [1,] 1 7 [2,] 1 8 [3,] 2 7 [4,] 2 8 [5,] 3 7 [6,] 3 8 > I want to generalize this to any number of arguments, for example, <fantasy> > ntuple(c(1,2,3),c(7,8),c(14,15)) [,1] [,2]

Hello everybody Is there a good way for a function to tell whether the caller used the defaults? I'm writing a little function that may take a pair of real arguments or a single complex argument (in which case I want the real and imaginary components). "e" <- function(first,second=first) { if (all(first == second) & is.complex(first)) {

Dear Helplist Some time ago, Professor Ripley gave me a tip which I thought was very very useful for Monte Carlo simulation; I thought I'd pass it on to the list, and ask whether this or a similar example could be added to the sapply() manpage. Suppose I have ten N(0,1) random variables and I'm interested in the pair that are closest together: R> min(diff(sort(rnorm(10)))) [1]

Hello All: The function expand.grid() does nearly exactly what I want for permutation tests I wish to carry out, and it does so quickly when the number is kept small as in the example below: expand.grid(rep(list(c(-1, 1)), 3)) Var1 Var2 Var3 1 -1 -1 -1 2 1 -1 -1 3 -1 1 -1 4 1 1 -1 5 -1 -1 1 6 1 -1 1 7 -1 1 1 8 1 1 1 Understandably,

I need to construct all possible combinations of an vector of length N taken X at a time for simulation purposes. Taking a a small vector as an example: >input <- c('a','b','c','d') >somefunction(input) a,b,c a,b,d a,c,d b,c,d my only solution thus far is: somefunction <- function(x){ ...a series of grotesque and horribly inefficient loops

Hello, I wonder if someone could send me suggestions on how to solve the following problem: I have a vector of an arbitrary size (ex. data<-c(10,10,11,10,12,11,10,12,11,11,10,11)) and use the table function, which gives the following result 10 11 12 5 5 2 that''s fine, but what I would like to do now is: construct new classes based on the number of classes from table, 10