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should have added: dim(x)[2L] -> length(x)
Am 31.03.20 um 16:21 schrieb Prof. Dr. Matthias Kohl:
Dear Ivan,
if I enter ncol in the console, I get
function (x)
dim(x)[2L]
indicating that function dim is called. Function dim has a method for
data.frame; see methods("dim").
T
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sequence alignment.
To get a first impression try:
vignette("RFLPtools")
as well as
library(RFLPtools)
example("RFLPplot")
example("RFLPrefplot")
Best regards,
Fabienne
Alexandra
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ce check time ...
- some minor corrections in ExamplesEstimation.R in folder scripts
Best
Peter
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vignette:
* included an example with escape sequences in vignette
* included an example with framed code in vignette
Best
Peter
Matthias
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r-packa.
Introduction to Metabolomics and biomarker research.
The course will take place in Innsbruck, 16th to 17th November 2009, and
will be held in German.
For more details see:
http://www.gdch.de/vas/fortbildung/kurse/fortbildung2009.htm#1175
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search on whether there's a way to
computer
the median for each row of a nxn matrix and return the medians for
each row
for further computation.
And also if the number of columns in the matrix are even, how could I
specify which median to use?
Thank you very much!
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g the slot r (eg the one borrowed from the sn package in
your example); is it a problem? isn't it sufficient to give slot d,
and then you have automatic methods implemented to get from d() to r()
slots etc. is that right?
Thanks a lot for your help and time !
Best,
Guillaume
Matth
uot;, function(object)
obj...@mu) : no existing definition for function "mu"
I don't understand because to me mu is a parameter not a function...
maybe that is too complex programming for me and I should switch to
implementing my likelihood by hand with numerical convolutions and
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and
tain covariates in a regression
model), and results in overstated confidence of the final estimates by
not taking into account the imprecision in the normalizing factors.
Frank
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;NULL"))
setClass("c1", representation(value = "aovOrNULL"))
y1 = new("c1", value = NULL)
#trying to assign an aov object to the slot doesn't work
utils::data(npk, package="MASS")
npk.aov <- aov(yield ~ block + N*P*K, npk)
y2 = new("c1", value = n
or can somebody recommend an alternative?
Thanks
Rainer
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elp me?
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oes someone have example code for this or a similar problem? Is
this so
special that I have to get down to the lattice package?
Thank you,
Hans-Ulrich
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the following error message:
Error in image.default(1:nc, 1:nr, x, xlim = 0.5 + c(0, nc), ylim =
0.5 + :
dimensions of z are not length(x)(+1) times length(y)(+1)
-Peter
At 10:18 AM +0200 5/15/08, Matthias Kohl wrote:
Dear Peter,
heatmap.2(z, dendrogram = "none", Rowv = FALSE
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t; read the posting guide > > http://www.R-project.org/posting-guide.html> > and
> provide commented, minimal, self-contained, reproducible code.> > >
> _
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8 0.06.2
>> Year Totals 62.8 40.2 51.2 29.8 70.0 12.8 30.8 57.2 55.2 47.6 457.6
>>
>>
>>
>>
>> Be a better friend, newshound, and
>>
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Dear David,
no, distrTEst won't help. It has a different intention.
We are currently working on a new package "distrMod"
(cf. https://r-forge.r-project.org/projects/distrmod/)
which sometime might have such a functionality.
Best,
Matthias
David Bickel wrote:
> Is there any automatic mechanism f
Matthias Kohl wrote:
> one addition ...
>
>> Hello Ricardo,
>>
>> another solution could be using package distr:
>>
>> library(distr)
>> A <- c(18,18,18,19,20,21,22,23,24,25,26,27,28)
>> DA <- DiscreteDistribution(A)
&
one addition ...
> Hello Ricardo,
>
> another solution could be using package distr:
>
> library(distr)
> A <- c(18,18,18,19,20,21,22,23,24,25,26,27,28)
> DA <- DiscreteDistribution(A)
> # maybe
> # support(DA)
> # plot (DA)
>
> B <- c(82,83,84,85,85,86,87,88,89,90,91,91,92)
> DB <- DiscreteDistrib
Hello Ricardo,
another solution could be using package distr:
library(distr)
A <- c(18,18,18,19,20,21,22,23,24,25,26,27,28)
DA <- DiscreteDistribution(A)
# maybe
# support(DA)
# plot (DA)
B <- c(82,83,84,85,85,86,87,88,89,90,91,91,92)
DB <- DiscreteDistribution(B)
# support(DB)
# plot(DB)
DC <-
Dear Pedro,
you might be interested in the demo "StationaryRegressorDistr" of
package "distr".
library(distr)
demo("StationaryRegressorDistr")
hth,
Matthias
[EMAIL PROTECTED] wrote:
> Thanks Prof. Ripley.
>
> My apologies for not including the code.
>
> Below I illustrate my point using the G
Dear Milton,
package distrEx has methods to compute skewness.
library(distrEx)
?skewness
To generate new distributions you could use package distr.
hth,
Matthias
Milton Cezar Ribeiro wrote:
> Dear all,
>
> How can I generate values which distrituions have left or rigth skewness.
> After that,
Hello Rainer,
You could also get a very exact approximation using our package distr; e.g.
library(distr)
B1 <- Binom(prob = 0.4, size = 20)
B2 <- Binom(prob = 0.2, size = 10)
B3 <- B1+B2 #convolution!
plot(B3)
hth,
Matthias
Rainer M. Krug schrieb:
> Frede Aakmann Tøgersen wrote:
>
>> Perhaps
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