Displaying 6 results from an estimated 6 matches for "ysbl".
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sbl
2003 Sep 10
6
insert eps into microsft word
it seems that word can not read encapsupalted postscripts generated by R
I used this command
postscript("output.eps",horizontal=F,onefile=TRUE)
since onefile=TRUE produces an encapsualted postscript
actually what I'm trying to do is to insert the postsript file into a
word document
since other formats like jpeg and bmp do not reproduce the same quality
like postscript
formats
any
2005 Oct 26
4
symbolic math
Hi all!
Does anyone knows if it exists a "symbolic math" package in R, that allows to compute derivatives, integrals, etc.?
Does exist a freeware version of Maple?
Cheers,
Marco
[[alternative HTML version deleted]]
2003 Jul 23
2
Read trajectory file into R
dear helpers,
I wonder if there is a way to read a molecular dynamic trajectory file (
binary file) produced by CHARMM into R. Something like that in matlab.
Actually this will save tremendous effort in post processing.
best regards
karim
2006 Feb 22
0
ylim in dendrogram plot ... error
I'm trying to plot a dendrogram object which is created using
"as.dendogram" function. It works fine however I can not change the
yaxis limits of the plot.
tree<-as.dendrogram(hclust(as.dist(dissim),method="single"))
plot(tree,ylim=range(0,20))
Error in plot.default(0, xlim = xlim, ylim = ylim, type = "n", xlab =
xlab, :
formal
2003 Nov 09
1
weird behaviour of eigen()
I'm using R 1.7.1 under linux redhat
it seems that the eigen values produced by eigen() do not follow
a consistant order; I mean either ascending or discending
e.g
for one system:
eigenV<-eigen(V)
> print(eigenV$values)
[1] -7.706828e+13 -4.702980e+13 -3.267579e+13 -1.701297e+13
-8.041677e+12
[6] -5.707311e+12 -5.053941e+12 -4.774652e+12 -4.280423e+12
-3.798905e+12
2004 Oct 15
1
cluster analysis
Hello. I wonder if anyone can help me with this.
I'm performing cluster analysis by using hclust in stats package.
My data are contained in a data frame with 10 columns, named "drops".
Firs I create a distance matrix using dist:
distanxe <- dist(drops)
Then I perform cluster analysis via hclust:
clusters <- hclust(distanze)
At this point I want to view the tree