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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"

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

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

In 2.8.0/Windows Vista: When 'unique' gives a type error message, it prints out even if errors are being caught: > try(unique(quote(hello)),silent=TRUE) hello This comes from the .Internal unique routine: > try(.Internal(unique(quote(hello),NULL,NULL)),silent=TRUE) hello I guess it is using the internal equivalent of print rather than the internal equivalent of stop.

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 definition....

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)

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') ==

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

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)

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

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

...t. The R GUI series like Rattle come even closer to Excel...so a VBA _R_ExCel package might be useful to ordinary folks . Besides Excel costs money, so adding R functions to Open Office would help both of them ( if not attempted already) Regards, Ajay www.decisionstats.com On 1/8/09, Stavros Macrakis <macrakis at alum.mit.edu> wrote: >> >> "Some people familiar with R describe it as a supercharged version of >> Microsoft's Excel spreadsheet software..." >> > > It is easy to ridicule this line from the NYT article. But this is not only > a v...

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

The documentation for is.atomic and is.recursive is inconsistent with their behavior in R 2.9.1 Windows. ? is.atomic ???? 'is.atomic' returns 'TRUE' if 'x' is an atomic vector (or 'NULL') ???? and 'FALSE' otherwise. ???? ... ???? 'is.atomic' is true for the atomic vector types ('"logical"', ???? '"integer"',

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

read.table gives idiosyncratic results when the input is formatted strangely, for example: read.table(textConnection("a'b\nc'd\n"),header=FALSE,fill=TRUE,sep="",quote="'") => "c'd" "a'b" "c'd"

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 would like to apply a function 'f' to the lagged version of a vector and the vector itself. This is easy to do explicitly: mapply( f, v[-1], v[-length(v)] ) or in the case of a pointwise vector function, simply f( v[-1], v[-length(v)] ) This is essentially the same as 'diff' but with an arbitrary function, not '-'. Is there a standard way to do this? Is

If I have 2 n-dimensional arrays, how do I compose them into a n+1-dimension array? Is there a standard R function that's something like the following, but that gives clean errors, handles all the edge cases, etc. abind <- function(a,b) structure( c(a,b), dim = c(dim(a), 2) ) m1 <- array(1:6,c(2,3)) m2 <- m1 + 10 abind(m1,m2) ==> , , 1 [,1] [,2] [,3] [1,] 1 3 5

I have a file of data where each line is a series of name-value pairs, but where the names are not necessarily the same from line to line, e.g. a=1,b=2,d=5 b=4,c=3,e=3 a=5,d=1 I would like to create a data frame which lines up the data in the corresponding columns. In this case, this would be data.frame( a = (1, NA, 4), b = (2, 4, NA), c = (NA, 3, NA), d = (5, NA, 1), e = (NA, 3,