search for: ysbl

Displaying 6 results from an estimated 6 matches for "ysbl".

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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