similar to: increase symbol size in expression - axis label of a plot

Heja, I've some bigger distance-matrices like this: num [1:3231, 1:3231] 0.000 0.176 0.176 0.176 0.176 ... - attr(*, "dimnames")=List of 2 ..$ : chr [1:3231] "A" "B" "C" "D" ... ..$ : chr [1:3231] A" "B" "C" "D" . I actually want to convert them into a 2 column dataframe like this: data.frame':

Heja, I hope someone is still there to help me: How can I somehow merge/combine matrices to get such a result: Matrix A A B x1 1 0 x2 1 1 Matrix B C D x3 1 0 x4 0 1 Resulting Matrix? A B C D x1 1 0 0 0 x2 1 1 0 0 x3 0 0 1 0 x4 0 0 0 1 Does anyone see this probably obvious solution with R how to do this? Sorry if this question is silly...it's too hot here to think properly ;O)

HI! I?ve 3 vectors of different length (a,b,c) and want to arrange them in a matrix a,b,c as rows and the figures of these vectors in the columns (with that matrix i want to calculate a distance between thes vectors - vegan - vegdist - horn). Is there a possibilty to create such a matrix and to fill up the missing fields with NA?s automatically???? Thanx marten winter -- *Marten Winter*

dear all, I want to perform a posthoc test for my ANCOVA: a1<-aov(seeds~treatment*length) With summary(glht(a1, linfct = mcp(treatment = "Tukey"))) R tells me: "covariate interactions found -- please choose appropriate contrast" How do I build these contrasts? Ideally, I would like to have the posthoc test for the ANCOVA including a block-effect

Hello, I successfully used RODBC very frequently, but after having updatetd to R 6.0.2, the current RODBC-Version gives me some problems. After connecting to my Oracle-Database via odbcConnect("") (or the necessary information) I receive a much longer output than usual: RODB Connection 0 Details: case=nochange DRIVER={Oracle in OraHome90} ... with all the details. Previously,

Dear fellow R-users, I have the problem of being unable to repeatedly use a C++-function within R unless by dyn.unloading/dyn.loading it after each .C call. The C++-code (too large to attach) compiles without problem using R CMD SHLIB. It loads (using dyn.load("myfun.so")) and executes (via .C(myfun, ...) ) properly. The function returns no object, only reads files from disk,

Dear Tomas, Thanks for your commitment to fix this issue and also to add the chunk size as an argument. If you want our input, let us know ;) Best Regards On 02/26/2018 04:01 PM, Tomas Kalibera wrote: > Dear Christian and Henrik, > > thank you for spotting the problem and suggestions for a fix. We'll probably add a chunk.size argument to parLapplyLB and parLapply to follow OpenMP

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Dear all, I?m working as an administrator of a High-Performance Computing (HPC) Cluster which runs on Linux. A lot of people are using R on this Linux cluster and, of course, the *parallel* package to speed up their computations. It has been our collective experience, that using |makeForkCluster| yields an overall better experience /on Linux/ than the |makePSOCKcluster|, for whatever definition

Hi, I want to share a partition of an external disk between 3 machines. It is located on a Sun StoreTek 3510 and bound (via multipathing) to all 3 machines. One machine (say mach1) is the node I used to create the filesystem and setup /etc/ocfs2/cluster.conf. I copied the file to the other 2 machines. All use the same /etc/multipath.conf[1], too. All start /etc/init.d/ocfs2 at boot, all are

Dear R-Devel List, I have installed R 3.4.3 with the patch applied on our cluster and ran a *real-world* job of one of our users to confirm that the patch works to my satisfaction. Here are the results. The original was a series of jobs, all essentially doing the same stuff using bootstrapped data, so for the original there is more data and I show the arithmetic mean with standard deviation. The

Dear Henrik, The rationale is just that it is within these extremes and that it is really simple to calculate, without making any assumptions and knowing that it won't be perfect. The extremes A and B you are mentioning are special cases based on assumptions. Case A is based on the assumption that the function has a long runtime or varying runtime, then you are likely to get the best load

Dear R-Devel List, **TL;DR:** The function **parLapplyLB** of the parallel package has [reportedly][1] (see also attached RRD output) not been doing its job, i.e. not actually balancing the load. My colleague Dirk Sarpe and I found the cause of the problem and we also have a patch to fix it (attached). A similar fix has also been provided [here][2]. [1]:

Dear Christian and Henrik, thank you for spotting the problem and suggestions for a fix. We'll probably add a chunk.size argument to parLapplyLB and parLapply to follow OpenMP terminology, which has already been an inspiration for the present code (parLapply already implements static scheduling via internal function staticClusterApply, yet with a fixed chunk size; parLapplyLB already

Hi, I'm trying to understand the rationale for your proposed amount of splitting and more precisely why that one is THE one. If I put labels on your example numbers in one of your previous post: nbrOfElements <- 97 nbrOfWorkers <- 5 With these, there are two extremes in how you can split up the processing in chunks such that all workers are utilized: (A) Each worker, called

Hello, I created puppet class and I want the file operation to be executed on all servers but not on server with hostname "''server1.domain.com". I tried this class, but it does not work. Is there any other way? Thanks class test { if $hostname != ''server1.domain.com'' { file { "/etc/ntp.conf": owner

When I try to connect to my new puppet master, I get an error because of a self-signed certificate: ---snip--- # puppet agent --test --noop Warning: Unable to fetch my node definition, but the agent run will continue: Warning: SSL_connect returned=1 errno=0 state=SSLv3 read server certificate B: certificate verify failed: [self signed certificate in certificate chain for /CN=Puppet CA:

Hi R-Users, I posted this question a while ago on the bioconductor mailing list but got no answers. Maybe here is somebody who might know a solution: I failed at drawing multiple filters in a densityplot() using the FlowCore/FlowViz packages. I found a way to draw multiple filters in xyplot(), using the glpolygon method within the panel-function, but some similar attempts for densityplot

Dear R-users (and developers), I am looking for an efficient framework to carry out parameter estimations based on MCMC (optionally with specified priors). My goal is as follow: * take ANY R-function returning a likelihood-value (this function may itself call external programmes or other code!) * run a sampler that covers the multidimensional parameter space (thus creating a posterior

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