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Following Duncan's suggestion, I forward the below to R-devel. vQ -------- Original Message -------- Subject: Re: [R] Randomly remove condition-selected rows from a matrix Date: Fri, 02 Jan 2009 10:34:52 -0500 From: Duncan Murdoch <murdoch at stats.uwo.ca> To: Wacek Kusnierczyk <Waclaw.Marcin.Kusnierczyk at idi.ntnu.no> CC: R help <R-help at stat.math.ethz.ch> References: <79CAFBDD-4BB8-4C9D-A0E9-54E280458510 at gmail.com> <8b356f880812300920o19d18aeo47dc31f087c3f36 at mail.gmail.com> <DA6ECC19-C786-4C02-B246-4B613726BC7F at gmail.com> <8b356f88081...

the following is a trivialized version of some functional code i tried to use in r: (funcs = lapply(1:5, function(i) function() i)) # a list of no-parameter functions, each with its own closure environment, # each supposed to return the corresponding index when applied to no arguments sapply(funcs, function(func) func()) # supposed to return c(1,2,3,4,5) there is absolutely nothing unusual in

Dear R Gurus: How do I find the functions which are primitives, please? Thanks, Edna Bell

Hi all I have the following regular expression problem: I want to find complete elements of a vector that end in a repeated character but where the repetition doesn't make up the whole word. That is, for the vector vec: vec<-c("aaaa", "baaa", "bbaa", "bbba", "baamm", "aa") I would like to get "baaa" "bbaa"

I am wondering if people on the list could recommend books that they have found helpful about programming concepts and style? I often find that students write R programs by copying existing code but could really benefit from the understanding of more general programming ideas. An example would be to avoid writing functions which attempt to modify their parameters. Another principle would be

Dear R Gurus: I read somewhere that functions are considered vectors. Is this true, please? thanks Edna Bell

Full_Name: Wacek Kusnierczyk Version: 2.10.0 r48365 OS: Ubuntu 8.04 Linux 32bit Submission from: (NULL) (129.241.110.141) sprintf has a documented limit on strings included in the output using the format '%s'. It appears that there is a limit on the length of strings included with, e.g., the format '%d' beyond which surprising things happen (output modified for conciseness):

given what ?identical says, i find the following odd: x = 1:10 y = 1:10 all.equal(x,y) [1] TRUE identical(x,y) [1] TRUE y[11] = 11 y = y[1:10] all.equal(x,y) [1] TRUE identical(x,y) [1] FALSE y [1] 1 2 3 4 5 6 7 8 9 10 length(y) [1] 10 looks like a bug. platform i686-pc-linux-gnu arch i686 os linux-gnu system

?ginv provides 'Modern Applied Statistics with S' (MASS), 3rd, by Venables and Ripley as the sole reference. I happen to have this book (4th ed) on loan from our library, and as far as I can see, ginv is mentioned there twice, and it is *used*, not *explained* in any way. (It is used on p. 148 in the 4th edition.) ginv does not appear in the index of MASS. ginv is an implementation of

m = matrix(1:4, 2) apply(m, 1, cat, '\n') # 1 2 # 3 4 # NULL why the null? vQ

Dear all, let's assume I have a vector of character strings: x <- c("abcdef", "defabc", "qwerty") What I would like to find is the following: all elements where the word 'abc' does not appear (i.e. 3 in this case of 'x'). Since I am not really experienced with regular expressions, I started slowly and thought I find all word were

the man page for relational operators (see, e.g., ?'<') says: " Binary operators which allow the comparison of values in atomic vectors. Arguments: x, y: atomic vectors, symbols, calls, or other objects for which methods have been written. " it is somewhat surprizing that the following works: '<'(1) # logical(0) '<'() #

the man page for relational operators (see, e.g., ?'<') says: " Binary operators which allow the comparison of values in atomic vectors. Arguments: x, y: atomic vectors, symbols, calls, or other objects for which methods have been written. " it is somewhat surprizing that the following works: '<'(1) # logical(0) '<'() #

On Fri, Apr 24, 2009 at 14:40, Wacek Kusnierczyk <Waclaw.Marcin.Kusnierczyk at idi.ntnu.no> wrote: > maechler at stat.math.ethz.ch wrote: >> >> =A0 =A0 vQ> sprintf has a documented limit on strings included in the ou= tput using the >> =A0 =A0 vQ> format '%s'. =A0It appears that there is a limit on the leng= th of st...

I wrote As a beginner, I agree .... the for loop is much clearer to me. Wacek Kusnierczyk <Waclaw.Marcin.Kusnierczyk at idi.ntnu.no> replied > >well, that's quite likely. especially given that typical courses in >programming, afaik, include for looping but not necessarily functional >stuff -- are you an r beginner, or a programming beginner? > Both. My PhD is in psych...

Full_Name: Wacek Kusnierczyk Version: 2.8.0 and 2.10.0 r48163 OS: Ubuntu 8.04 Linux 32bit Submission from: (NULL) (129.241.198.172) the following code illustrates a problem with sprintf which consistently causes a segfault when applied to certain type of arguments. it also shows inconsistent consequences of the segfault: (e = tryCatch(stop(), error=identity)) # e is an error object

Tested in: R version 2.8.1 (2008-12-22) / Windows Recursive default argument references normally give nice clear errors. In the first set of examples, you get the error: Error in ... : promise already under evaluation: recursive default argument reference or earlier problems? (function(a = a) a ) () (function(a = a) c(a) ) () (function(a = a) a[1] ) () (function(a = a)

Hello, I am wondering about the behaviour of strsplit. When the pattern matches the beginning of the search string, the mepty string is added to the result, but that's not the case when the pattern matches the end of the search string: strsplit(" hello dolly ") [1] "" "hello" "dolly" The man for strsplit explains the algorithm: " The algorithm

somewhat related to a previous discussion [1] on how 'names<-' would sometimes modify its argument in place, and sometimes produce a modified copy without changing the original, here's another example of how it becomes visible to the user when r makes or doesn't make a copy of an object: x = NULL dput(x) # NULL class(x) = 'integer' # error: invalid

Dear R users, Can anyone please tell me how to generate a large number of samples in R, given certain distribution and size. For example, if I want to generate 1000 samples of size n=100, with a N(0,1) distribution, how should I proceed? (Since I dont want to do "rnorm(100,0,1)" in R for 1000 times) Thanks for help Debbie