Hi all,
I would like to aggregate a large data file that is defined by a number of
factors and associated values. The point is that not all factor level
combinations are present in the data file -- these missing values are in
fact to be treated as zeroes.
Is there a straightforward way to
Hi all,
I'd like to plot a set of data (x,y,z) as 3D-cloud, and add several line
plots to the same 3D graph:
Two questions:
1) How do I connect points to get a line?
cloud(z~x*y,data=d,zlim=c(0,1))# works
cloud(z~x*predict(l),data=d,zlim=c(0,1),type=l) # type=l doesn't
Warning
Hi all,
I posted this question several days ago, but did not get any answer
until now. Since I still have no clue about the source of this error
message, I repost a description of the problem including some code:
A student at our institute fitted an aov model, and got the following
error
Hi all,
A student at our institute asked me for help with the following problem:
After fitting an aov model, she wanted diagnostic plots, and got the
following error message:
plot(p.aov)
Hit Return to see next plot:
Hit Return to see next plot:
Error in plot.window(xlim, ylim, log, asp, ...)
Hi all,
Using Xemacs/ESS (Xemacs 21.4-12/ESS 5.1.24), I noticed that tab
completion does not work for file names.
df - read.csv(xx [TAB]
doesn't complete the file name.
After hitting TAB, I get last thing matched was not a buffer in the
status bar. Any idea what may go wrong?
Thanks for
Sean Davis wrote:
I don't think that this works within the R process buffer, but I could be
wrong. Does the documentation say that it should somewhere?
Sean
The ESS doc says (section 3.2):
Completion is also provided over file names, which is particularly
useful when using S functions such
Is there a way to prevent the re-ordering of factors by aov? I do have a
three-way interaction that I do want to fit before a two-way interaction
(different factors, so they are not nested), but R moves the two-way
interaction to the front. I know it generally makes sense to fit the
two-way
Running lme on your data set results exactly in what you expect - or do
you expect something different?
Pascal
L1-factor(F1f)
L2-factor(F2f)
L3-factor(F3f)
lme(value ~ 1,random = ~ 1 | L1/L2/L3)
Linear mixed-effects model fit by REML
Data: NULL
Log-restricted-likelihood: 438.9476
Fixed:
Hi all,
I tried to save a complete log of a R session we had in a seminar
today... but I didn't succeed.
1) R | tee session.log
This saves both input and output, but I do get the cursor key escape
sequences from editing (cursor-up to get last command etc) instead of
the actual command line
Martin Wegmann wrote:
Dear R-user,
I already received quite a lot of replies to this mail and like to do a
preliminary sum up.
A few were sceptical about the use of such a beginner mailing list.
The arguments were that people starting with R will only stay subscribed for
a short time
Hi all,
is there an easy way to build up a data frame by sequentially adding
individual rows? The data frame consists of numeric and character
columns. I thought of rbind, but I ended up with numeric values for the
character columns.
Pascal
__
Martin Maechler wrote:
Pascal == Pascal A Niklaus [EMAIL PROTECTED]
on Mon, 08 Dec 2003 11:47:02 +0100 writes:
Pascal Hi all, is there an easy way to build up a data
Pascal frame by sequentially adding individual rows?
yes, pretty easy, but usually not recommended because
Karl Knoblick wrote:
Dear R-community!
I still have the problem reproducing the following
example using lme.
id-factor(rep(rep(1:5,rep(3,5)),3))
factA - factor(rep(c(a1,a2,a3),rep(15,3)))
factB - factor(rep(c(B1,B2,B3),15))
Y-numeric(length=45)
Y[ 1: 9]-c(56,52,48,57,54,46,55,51,51)
Prof Brian Ripley wrote:
On Sat, 29 Nov 2003 [EMAIL PROTECTED] wrote:
Hi all,
I'd like to extract a value from an ANOVA table, but experience the following
problem:
### This works:
s.pseudo - summary(aov(m ~ block + mix*graz,data=split1))
s.pseudo
Df Sum Sq Mean Sq F
Hi all,
Given a number of points (x,y) in a plane, I'd like to plot a map of
polygons, so that
1) each polygon contains exactly one point
2) the polygon defines the area for which this specific point is
closer than any other point.
It's a bit like a map of areas influenced by that
Hi all,
Is there a function to check if a particular value is contained in a
vector? I've looked at grep in the hope that I could use a Perl-like
syntax, but obviously it's different...
I'd like to do something like:
y - c(a,b,c)
if(a in y)
{
# a is not in y
}
Also, is
Hi all,
Thanks for the incredibly quick help with the %in%...
There's a second question, though: I'd like to increment an element of a
vector if a certain event occurs, e.g.
count[event] - count[event] + 1; # works, but...
Is this efficient? I wonder whether R needs to subset the
The postscript device behaves strangely - is this possibly a bug?
case 1)
postscript(gfx-%d.ps,width=8 , height=5, paper=special,
horizontal=F, onefile=FALSE);
some plots here
dev.off()
The first plot is in portrait orientation
The second and all the following plots are in landscape
Pascal A. Niklaus wrote:
Hi all,
I'm not sure how to correctly analyse the following data with glm, and
hope for some advice from this list, ideally showing how to specify
the model in R and perform the tests, and also for suggestions of
literature.
The data structure is like this:
- 20
summary(lm(x ~ I(t^2))), but you should probably read the Introduction
to R
Pascal
__
[EMAIL PROTECTED] mailing list
https://www.stat.math.ethz.ch/mailman/listinfo/r-help
Hi all,
I'm not sure how to correctly analyse the following data with glm, and
hope for some advice from this list, ideally showing how to specify the
model in R and perform the tests, and also for suggestions of literature.
The data structure is like this:
- 20 plant populations were
As far as I understand it, the problem is that REML accounts for the
degrees of freedom used up by fixed effects (e.g., treatments), whereas
ML does not account for these. From that perspective, REML appears to be
the better fitting method.
However, if you test for a fixed effect by comparing
Hi all,
I repeatedly encounter the following problem: After importing a data set
into a data frame, I wish to set a column with numeric values to be a
factor, but can't figure out how to do this. Also, I do not wish to
write as.factor(x) all the time. I can create a new vector with x -
You need to know the exact distribution of the random numbers you want
to generate. For rnorm, in fact, you do not just specify the mean and
the variance, but implicitely also that the data is normally
distributed. Likewise, it is not sufficient to give min, max, skewness
etc, you also need to
lme should do the job (r1,r2,r3 are your random factors):
library(nlme)
y.lme - lme(y ~ 1,random = ~ 1 | r1/r2/r3)
summary(y.lme)
This is equivalent to a call to varcomp in S-Plus
Pascal
--
Dr. Pascal A. Niklaus
Institute of Botany
University of Basel
Schönbeinstrasse 6
CH-4056 Basel
Hi all,
I wonder how to correctly write the following expression (it's the axis
label in a plot command):
ylab=expression(y' == y - bar(y) )
Somehow the single quote in y' is causing the problems, I guess because
it is interpreted as a quote...
Does it have to be escaped? But how?
Thanks
Hi all,
Is there a way to rotate a plot, e.g. a histogram, by a certain angle
(90/180/270 degress)? I spent hours trying to figure out how this is
done, but without success.
Also, I'm looking for an equivalent to the S-Plus subplot command to
insert a kind of thumbnail graphic into a bigger
(y.anova)
In R, it fails with the following error:
levels(CO2)
[1] A C E
y.anova - aov(y + C(CO2,c(1,0,-1)) )
Error in contrasts-(*tmp*, value = contr) :
wrong number of contrast matrix rows
What is the way to do this in R?
Thanks
Pascal
--
Dr. Pascal A. Niklaus
Institute
Thanks for the reply. Below is the solution and the S-Plus and R code
that does the same (for documentation).
I can't reproduce that in S-PLUS 6.1, and it is not as documented:
In S-Plus 2000, C() complements the contrast matrix with orthogonal
contrasts if only the first is given.
CO2 -
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