I fiddled around and found this solution, which is far from elegant,
but it doesn't require you to know the factor levels in advance.
t <- with(DF, tapply(as.character(X), Y, table))
lapply(t, function(x)
table(strsplit(paste(names(x),collapse=""),split="")))
Darin
On Fri, Sep 10, 2010 at
I've found using the arm package to be very useful.
require(arm)
then use ranef(Full_model) and fixef(Full_model)
On Wed, Sep 22, 2010 at 05:39:41PM +1000, Lorenzo Cattarino wrote:
> Hi again,
>
>
>
> Sorry, probably I was not clear enough.
>
>
>
> I was wondering if there is a way in R
I think you can use the bootstrap to obtain the std error. My
attempt for your problem and data is below. I would be interested if
anyone can point out a problem with this approach.
Darin
y=rbinom(100,1,.4)
x1=rnorm(100, 3, 2)
x2=rbinom(100, 1, .7)
diff <- vector(mode="numeric", length=200)
for
Or at least is seems that way to me. It's not a big problem, but the
behavior doesn't match the documentation. (I think r-help is the
place to report this. )
> x <- factor(1:5)
> x.ro <- reorder(x, rnorm(5))
> is.ordered(x.ro) # should be FALSE according to ?reorder
[1] TRUE
>
> x.ro <- reorder(
sion 2.11.1 (2010-05-31)
>> i486-pc-linux-gnu
>>
>>> x <- factor(1:5)
>>> x.ro <- reorder(x, rnorm(5))
>>> is.ordered(x.ro)
>> [1] FALSE
>>> x.ro <- reorder(x, rnorm(5), ordered=FALSE)
>>> is.ordered(x.ro)
>> [1]
No.
> ?sample
to see what sample() does.
On Tue, Oct 19, 2010 at 02:59:05AM -0700, emj83 wrote:
>
> Hi,
>
> Please can someone tell me if using sample() in R is actually a quick way of
> doing the Inverse Transform Sampling Method?
>
> Many thanks Emma
> --
> View this message in context
My impression is that varclus from the Hmisc library is very
convenient to use when you want to get an idea of the correlation
among predictor variables in a regression setting, but if you want
to perform cluster analysis in general, you may be better off using
a different function in R, such as hc
coef(mod1)$bird will give you a matrix with two columns. The first
column is the intercept for each bird and the second column is the
slope for each bird.
ranef(mod1) will also give you a matrix of two columns. These
represent the random effects. That is, how much the intercept (or
slope) is shift
t; Many Thanks
> >
> > Sam
> >
> > Dr Samantha Patrick
> > EU INTERREG Post Doc
> > Davy 618
> > Marine Biology & Ecology Research Centre
> > University of Plymouth
> > Plymouth
> > PL4 8AA
> >
> > T: 01752 586165
> > M:
On Wed, Jan 07, 2009 at 08:00:28AM -0600, Frank E Harrell Jr wrote:
> This is great to see. It's interesting that SAS Institute feels that
> non-peer-reviewed software with hidden implementations of analytic
> methods that cannot be reproduced by others should be trusted when
> building aircraf
Have you tried using the cosine of the angle between two
observations as the similarity measure? If you want to account for
magnitudes, there is something called the jaccard coefficient (if I
remember correctly) that can be used.
Darin
On Mon, Jan 26, 2009 at 10:41:40AM +0100, mau...@alice.it wro
Search the R mailing list archive for other reports of success on
AIX. I compiled a 64-bit version of R-2.8.0 successfully with the
following options:
export OBJECT_MODE=64
export CC="xlc_r -q64"
export CFLAGS="-O -qstrict"
export CXX="xlC_r -q64"
export CXXFLAGS="-O -qstrict"
export F77="xlf_r -q
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