similar to: Definition of = vs. <-

Inspired by Rudolf Biczok's query of Fri, Jan 23, 2009 at 1:25 AM, I tried to implement iteration in a generic way using S4. (Though I am admittedly still struggling with learning S4.) > setClass("foo",representation(bar="list")) [1] "foo" > x<-new("foo",bar=list(1,2,3)) Given this, I would not expect for(i in x)... to work, since R has no way

I was surprised to find that df$a[1] is an order of magnitude faster than df[1,"a"]: > df <- data.frame(a=1:10) > system.time(replicate(100000, df$a[3])) user system elapsed 0.36 0.00 0.36 > system.time(replicate(100000, df[3,"a"])) user system elapsed 4.09 0.00 4.09 A priori, I'd have thought that combining the row and column

There seems to be a funny interaction between lapply and "$" -- also, "$" doesn't signal an error in some cases where "[[" does. The $ operator accepts a string second argument in functional form: > `$`(list(a=3,b=4),"b") [1] 4 lapply(list(list(a=3,b=4)),function(x) `$`(x,"b")) [[1]] [1] 4 ... but using an lapply "..."

The semantics of [ and [[ don't seem to be fully specified in the Reference manual. In particular, I can't find where the following cases are covered: > cc <- c(1); ll <- list(1) > cc[3] [1] NA OK, RefMan says: If i is positive and exceeds length(x) then the corresponding selection is NA. > dput(ll[3]) list(NULL) ? i is positive and exceeds length(x); why isn't this

I have two vectors, a and b. b is a text file. I want to find in b those elements of a which occur at the beginning of the line in b. I have the following code, but it only returns a value for the first value in a, but I want both. Any ideas please. a = c(2,3) b = NULL b[1] = "aaa 2 aaa" b[2] = "2 aaa" b[3] = "3 aaa" b[4] = "aaa 3 aaa"

Since both comparison and negation are well-defined for time differences, I wonder why abs and division are not defined for class difftime. This behavior is clearly documented on the man page: "limited arithmetic is available on 'difftime' objects"; but why? Both are natural, semantically sound, and useful operations and I see no obvious reason that they should give an error:

Since both comparison and negation are well-defined for time differences, I wonder why abs and division are not defined for class difftime. This behavior is clearly documented on the man page: "limited arithmetic is available on 'difftime' objects"; but why? Both are natural, semantically sound, and useful operations and I see no obvious reason that they should give an error:

I recently traced a bug of mine to the fact that cumsum(s)[length(s)] is not always exactly equal to sum(s). For example, x<-1/(12:14) sum(x) - cumsum(x)[3] => 2.8e-17 Floating-point addition is of course not exact, and in particular is not associative, so there are various possible reasons for this. Perhaps sum uses clever summing tricks to get more accurate results? In some

To test two environments for object equality (Lisp EQ), I can use 'identity': > e1 <- environment(local(function()x)) > e2 <- environment(local(function()x)) > identical(e1,e2) # compares object identity [1] FALSE > identical(as.list(e1),as.list(e2)) # compares values as name->value mapping [1] TRUE # (is there a

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)

What is the recommended class for time of day (independent of calendar date)? And what is the recommended way to get the time of day from a POSIXct object? (Not a string representation, but a computable representation.) I have looked in the man page for DateTimeClasses, in the Time Series Analysis Task View and in Spector's Data Manipulation book but haven't found these. Clearly I can

On Tue, Feb 10, 2009 at 10:11 AM, Duncan Murdoch <murdoch at stats.uwo.ca> wrote: > Stavros Macrakis wrote: >> On Tue, Feb 10, 2009 at 8:31 AM, Duncan Murdoch <murdoch at stats.uwo.ca>wrote: >>> The evaluator recognizes the context of usage and will get the >>> function for a function call.... >> Can you point me to chapter and verse in the language

What is the 'idiomatic' way of writing a vectorized switch statement? That is, I would like to write, e.g., vswitch( c('a','x','b','a'), a= 1:4, b=11:14, 100 ) => c(1, 100, 13, 4 ) equivalent to ifelse( c('a','x','b','a') ==

Judging from the traffic on this mailing list, a lot of R beginners are trying to write things like assign( paste( "myvar", i), ...) where they really should probably be writing myvar[i] <- ... Do we have any idea where this bizarre habit comes from? -s

I was wondering what the criteria were for including books on the Books Related to R page <http://www.r-project.org/doc/bib/R-books.html>. (There is no maintainer listed on this page.) In particular, I was wondering why the following two books are not listed: * Andrew Gelman, Jennifer Hill, *Data Analysis Using Regression and Multilevel/Hierarchical Models*. (CRAN package 'arm') *

I've read in many places that R semantics are based on Scheme semantics. As a long-time Lisp user and implementor, I've tried to make this more precise, and this is what I've found so far. I've excluded trivial things that aren't basic semantic issues: support for arbitrary-precision integers; subscripting; general style; etc. I would appreciate corrections or additions from

Is there a generic binary search routine in a standard library which a) works for character vectors b) runs in O(log(N)) time? I'm aware of findInterval(x,vec), but it is restricted to numeric vectors. I'm also aware of various hashing solutions (e.g. new.env(hash=TRUE) and fastmatch), but I need the greatest-lower-bound match in my application. findInterval is also slow for

A table without names displays like a vector: > unname(table(2:3)) [1] 1 1 1 and preserves the table class (as with unname in general): > dput(unname(table(2:3))) structure(c(1L, 1L), .Dim = 2L, class = "table") Does that make sense? R is not consistent in its treatment of such unname'd tables: In plot, they are considered erroneous input: >

At one point I believe I heard of an R package that would automatically find the most empty space in a plot, and then that answer could then be used to intelligently place a legend. I would like to try to apply that R package to the contrived example shown below, so thank you for any hints or tips that can be provided. x = seq(0, 1000, by = 1) y1_vals<-rnorm(1000, mean = 0, sd = 50)

The R FAQ is very helpful about installing R on various Linuxes, but doesn't seem to discuss the advantages of one distribution over another. I am new to Linux (though not to Unix!), and would appreciate some guidance from those with experience. I plan to set up a headless Linux x86 server for the sole purpose of running 64-bit R. Are there reasons to prefer some Linux distributions over