[Rd] get number of clusters

2008-03-15 Thread Stefan Tomzeck
hello,
i've a set of integers, e.g. x={1,2,3,2,3,100,101,104}
I want to compute now the numbers of the clusters via gap statistic.
I 've seen the commend gap. How can i use it? it doesn'work. I've loaded the 
the package gap and SAGx. But R does'nt recognize the command gap. 
Is it actually the right command to estimate the number of clusters?
 
Thanks a lot!!
 
_


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[Rd] Experimental R_has_slot() utility

2008-03-15 Thread Laurent Gautier
Dear list,


The utility R_has_slot mentioned in the file NEWS
(Experimental  R_has_slot() utility supplementing R_do_slot())
appears to be missing from a fresh checkout of the development branch.

$ svn up
At revision 44759.
$ grep -i has_slot `find include -name '*.h'`
$ grep -i _slot `find include -name '*.h'`
include/Rdefines.h:#define GET_SLOT(x, what)   R_do_slot(x, what)
include/Rdefines.h:#define SET_SLOT(x, what, value)
R_do_slot_assign(x, what, value)
include/Rinternals.h:SEXP R_do_slot(SEXP obj, SEXP name);
include/Rinternals.h:SEXP R_do_slot_assign(SEXP obj, SEXP name, SEXP value);


..or did I miss it ?

Thanks,


L.

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Re: [Rd] [patch] add=TRUE in plot.default()

2008-03-15 Thread Christos Hatzis
Andrew,

Here's is a way how your example could be coded with the current
implementation of plot.  You can always start with an empty plot and then
add lines or points (or both) using the corresponding functions.  

 x - seq(-2, 2, 0.1)
 plot(x, x, type=n)
 mapply(function(f, i) lines(x, f(x), col=i), functions, 1:3)

The current approach saves specification of a couple of parameters that
would otherwise had to be specified, since lines(...) would be equivalent to
plot(..., type=l, add=TRUE), and I think that this adds to clarity.

-Christos
 
 -Original Message-
 From: [EMAIL PROTECTED] 
 [mailto:[EMAIL PROTECTED] On Behalf Of Andrew Clausen
 Sent: Sunday, March 16, 2008 12:05 AM
 To: Duncan Murdoch
 Cc: R-devel@r-project.org
 Subject: Re: [Rd] [patch] add=TRUE in plot.default()
 
 Hi Duncan,
 
 On Mon, Mar 10, 2008 at 08:51:23AM -0400, Duncan Murdoch wrote:
  The add parameter only interacts with other parameters 
 superficially 
  -- some parameters of plot (like log) are related to the 
 shape of 
  the axes, and should be inherited from what is on the plot already.
  
  I'd say causing some parameters to be completely ignored without a 
  warning is more than a superficial interaction.
 
 Fair enough.  I suppose you could inadvertantly put leave 
 add=TRUE in some code, and wonder why axes aren't getting drawn.
 
  Really, add=TRUE is not
  a great design:  it would be better to say plot methods draw a new 
  plot (so they need args for all the decorations like axes, titles, 
  etc.), and have other ways to add things to plots.
 
 I don't like the idea of having a separate way to add to plots.
 I like the look of this code:
 
   f - function(x) x^2
   g - function(x) 1/x - 1
   h - function(x) x
   functions - c(f, g, h)
   for (i in 1:length(functions))
   plot(functions[[i]], add=i1, col=i)
 
 Of course, I'd prefer something like
 
   plot.new()
   for (i in 1:length(functions))
   plot(functions[[i]], add=TRUE, col=i)
 
 but that seems out of reach for compatibility reasons.
 
 How would you write this code in R today?
 
   Hadley was right on
  this, his ggplot2 has a better thought-out design than 
 classic graphics. 
However, we have what we have.
 
 I'm sure ggplot2 is vastly better, although I couldn't find a 
 quick intro.
 (Typing ggplot2 examples into Google didn't help me.)  
 Since plot() isn't deprecated yet, it's worth making cheap 
 useful improvements.
 
  I agree.  Adding an add=FALSE parameter to plot() would generate 
  errors for methods that don't implement it, so they would 
 all have to 
  be changed simultaneously, including in private/unreleased code.
  
  So I'd like to settle for second best: adding add=FALSE 
 parameters to 
  many plot methods.
  
  I like that suggestion better than adding it here and 
 there, one at a 
  time.  So, to advance the discussion:  can you take a look 
 at the plot 
  methods that are in the base and recommended packages, and work out 
  how many already have it, how many would be improved if it 
 was added, 
  and in how many cases it just wouldn't make sense?  (You 
 could also do 
  this on all the CRAN and Bioconductor packages, but that would be 
  about 100 times more work: about 50 times as many packages, 
 and much 
  less consistency in the programming and documentation standards.  
  Maybe on a subset of popular ones, e.g. those that Rcmdr suggests?)
 
 I had a quick look at the base packages.  (I did a crude 
 search with find and grep on the R source tarball.)  I 
 attached the full list.  There were 40 files
 containing plot methods.   Of these, 9 already implemented 
 add=TRUE explicitly
 and a further 9 inherited it from other plot methods that 
 could or already do implement it.  There were 2 methods for 
 which it clearly makes no sense.  For example, plot.lm makes 
 no sense because it does several separate plots, one after the other.
 
 It looks reasonably straightforward to implement most of the 
 remaining methods.
 I must confess I don't understand what all of these plots are 
 doing from a statistics point of view, but I suppose this 
 shouldn't matter.  (Econometrics uses different language...)
 
  Data like that could make a convincing argument that the effort of 
  adding this to the base packages is worthwhile.  (To get it 
 added to 
  non-base packages will require you to convince their 
 maintainers that 
  it's a good idea.)  Another helpful part of the argument 
 will be for 
  you to volunteer to do the work of both code and 
 documentation updates.
 
 I'm not very excited about doing work outside of base.  I can 
 do the base code + documentation though.  Any volunteers?
 
 Cheers,
 Andrew
 


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