similar to: Regarding the recent changes to @<-

Dear R-people: François Michonneau's method to obtain the special character plus/minus works on Windows 2000 professional. Many Thanks to François for his work! Phil Smith Centers for Disease Control and Prevention Atlanta, GA _____ From: François MICHONNEAU [mailto:francois.michonneau@gmail.com] Sent: Monday, March 20, 2006 1:58 PM To: r-help@stat.math.ethz.ch; Smith, Phil

Hi all, I am attempting to install a package called phylobase from source directory. It all seems to work until the end, at which point it looks like the last compile command fails because the line is too long...perhaps because the g++ command line also includes "Loading ~/.Rprofile...", like this: ============================ g++ -arch i386 -dynamiclib

Hello, Can anyone explain me what is wrong in the following code? and in particular why it is not possible to change the class of an object thanks to the function with(). Does an alternative exist? xxx <- data.frame(x = c("a","b","c","d","e"), y = c("1","2","3","4","5")) str(xxx) with(xxx, {

Hello. I want to create a list of vectors but each component of the list has a different length. For example: Example=list() Example=list(Example,c(1,2,3)) Example=list(Example,c(11,12,13,14,15)) If I want the first component of the Example list, I have to write: Example[[1]][[2]]. R responses 1 2 3 The second component: Example[[2]]: 11 12 13 14 15 If I iterate the previous example,

Hello, I would like to know what it means, when the hier.part's output has a data frame of a negative independent contribution for variables (?IJ) and how this can be caused. Thank you very much. Yours sincerely M. Heuner

Is there some reason why > (1:2)+(1:3) [1] 2 4 4 Warning message: In (1:2) + (1:3) : longer object length is not a multiple of shorter object length can't be made into an error? I realise it was there in S-PLUS, but since it produces a warning there can't be many examples on CRAN or Bioconductor using it, and I can't think of any situation where it would be used deliberately.

Dear list, here is a problem I met when trying to use a method for an S4 object, without loading the package in which the method was defined. I do not know if this is a bug, or a mistake of mine. Normally, I think the package in which the appropriate method is defined is loaded automatically when calling the method. The problem is that if the package is indeed loaded automatically, the

I'm in the process of converting some S3 methods to S4 methods. I have this function : setGeneric("enrichmentCalc", function(rs, organism, seqLen, ...){standardGeneric("enrichmentCalc")}) setMethod("enrichmentCalc", c("GenomeDataList", "BSgenome"), function(rs, organism, seqLen, ...) { ... ... ... })

Hi everyone I am trying to add a percent sign to my labels in a hist() plot. "labels = TRUE" gives me the values, but I don't know how to add the percent sign. I would prefer to annote the plot after drawing it, e.g. using text(), but don't know how to address the positions in a standard histogram. A lattice approach would work too. Best regards, LY -- View this message in

Hello All, Would like to be able to convert a matrix to a dataframe without losing an assigned dimname. Here is an example that should illustrate what I'm talking about. tableData <- state.x77[c(7, 38, 20, 46), c(7, 1, 8)] names(dimnames(tableData)) <- c("State", "") tableData State Frost Population Area Connecticut 139 3100 4862

The documentation for validObject suggests that slots are checked for validity, but validObject seems only to check that the slot has something claiming to be correct; validObject(obj) does not perform the equivalent of validObject(obj at y) for slot y. This is also the second problem issue reported in http://tolstoy.newcastle.edu.au/R/devel/05/03/0151.html Relevant documentation, an example,

Hi, When called with complete=TRUE, validObject() is supposed to work in a recursive manner. But here is a situation where it doesn't seem to be the case. Let's define a class with a validity method: setClass("PosInts", representation(ii="integer")) setValidity("PosInts", function(object) { if (!all(object at ii > 0))

2013/6/23 David Chisnall <David.Chisnall at cl.cam.ac.uk> > Hi, > > In our version of LLVM, we've added different-sized iPTR* types, so we > have an iPTR256 for our fat pointers. This causes some problems with > constraints, because the way that TableGen resolves constraints is not > expected to handle multiple pointer types. We've added a flag that can be >

I frequently get data sets with cryptically-named variables. The datasets are more useful to me with informative variable names. I know that I can rename variables using the following command: dimname(dataset[[2]][index.of.variable.to.be.renamed]<-new.variable.name If I want to do this inside a function (say something I call RenameCol) what is the best way to communicate the

Dear useRs and wizaRds, I am currently developing a set of functions using S4 classes. On the way I encountered the problem exemplified with the code below. For some reason the 'validity' method does not seem to work, i.e. does not check for errors in the specification of the slots of the defined class. Any hints? My understanding of the whole S4 system was that validity checks are made

Hello, Thomas Stabla (statho3@web.de) has already sent this question to R-help, Wed, 12 Nov 2003 21:21:31 +0100, but we are not sure whether we should better post this mail to this audience than to R-help: --------------------------------------------------------------------- We are using S4-classes and want to force a validity check when an object is created. How can this be done, when an

'methods' package feature request / discussion starter: perhaps a call to 'validObject' should occur at part of any slot replacement operation (and the operation not be carried out if it would invalidate the object)? this may prevent the need for prophylactic 'validObject' calls in other user-defined functions. in the example below, the slot assignment occurs

I think that the "dimname names" of tables and arrays could make aperm() and apply() (and probably some other functions) easier to use. (dimname names are, for example, created by table() ) The use would be something like: -- x <-table( from=sample(3,100,rep=T), to=sample(5,100,rep=T)) trans <- x / apply(x,"from",sum) y <- aperm( trans,

Suppose you have a class, say sex, for lack of a better example, and you are tempted, in defining the behavior of the call, is(x,"sex") to check whether certain basic features are satisfied, not to just trust the claim that x is specified to be of class "sex". `Without delving into details further sanity checking of the structure of the object is sometimes prudent to avoid

Further to the discussion between Murray Jorgensen and Brian Ripley, it seems to me better to choose tabulations that will not come and bite you. Suppose your data are sligtly irregular, e.g. (for the sake of the argument): data( warpbreaks ) warpbreaks$variant <- rep( 1:5, len=54 ) attach( warpbreaks ) tb <- table( wool, tension, variant ) tb # in this case you would like to see: tp