similar to: Error in expand.covs: 'data' must be an 'msdata' object

mzR is a Bioconductor package, so better to ask on the Bioconductor support forum https://support.bioconductor.org Oh, I see you did, and then the advice is to avoid cross-posting! The missing .o files would have been produced in an earlier compilation step; they likely failed in some way, so you need to provide the complete compilation output. Did you do this on a version of the package

I do this on a vanilla-clean R installation, simply: > biocLite("mzR") it pulls some deps in which compile fine, only mzR fails. ... meanwhile... I grabbed devtools and comiled github master - still fails. Should I attach build log? One should not send attachments to the list.. I don't suppose? On 21/12/16 17:06, Martin Morgan wrote: > mzR is a Bioconductor package, so

I'm not sure if I should bother you team with this, apologies in case it's a bother. I'm trying gcc 6.2.1 (from devtoolset-6) with R, everything seems to work just fine, except for mzR. Here is failed build: g++ -m64 -shared -L/usr/lib64/R/lib -Wl,-z,relro -o mzR.so cramp.o ramp_base64.o ramp.o RcppRamp.o RcppRampModule.o rnetCDF.o RcppPwiz.o RcppPwizModule.o RcppIdent.o

Hi everyone, I have this kind of raw dataset : - <Temp diffgr:id="Temp14" msdata:rowOrder="13"> <Date>2005-01-17T00:00:00+05:30</Date> <SecurityID>10149</SecurityID> <PriceClose>1288.40002</PriceClose> </Temp> - <Temp diffgr:id="Temp15" msdata:rowOrder="14">

I'm trying to convert a dataset from the time-independent analysis form > head(addicts) id clinic status survtime prison meth clinic01 1 1 1 1 428 0 50 1 2 2 1 1 275 1 55 1 3 3 1 1 262 0 55 1 into the "counting data format" necessary to perform extended Cox regression. I got

Dear R-users, Sorry for bothering you twice in a day, but I was wondering whether there is any R-function which can easily plot the single elements of a Lexis diagram. I though that Lexis.diagram(Epi) could be the case, but it just plot life times in a frame. In particular I have been searching for something similar to the function "image" which can plot either the single triangles of a

On Fri, Oct 21, 2016 at 01:58:55PM +0200, Christian Borntraeger wrote: > stop_machine can take a very long time if the hypervisor does > overcommitment for guest CPUs. When waiting for "the one", lets > give up our CPU by using the new cpu_relax_yield. This seems something that would apply to most other virt stuff. Lets Cc a few more lists for that. > Signed-off-by:

On Fri, Oct 21, 2016 at 01:58:55PM +0200, Christian Borntraeger wrote: > stop_machine can take a very long time if the hypervisor does > overcommitment for guest CPUs. When waiting for "the one", lets > give up our CPU by using the new cpu_relax_yield. This seems something that would apply to most other virt stuff. Lets Cc a few more lists for that. > Signed-off-by:

Some time ago commit 57f2ffe14fd125c2 ("s390: remove diag 44 calls from cpu_relax()") did stop cpu_relax on s390 yielding to the hypervisor. As it turns out this made stop_machine run really slow on virtualized overcommited systems. For example the kprobes test during bootup took several seconds instead of just running unnoticed with large guests. Therefore, the yielding was

On Fri, 21 Oct 2016 14:05:36 +0200 Peter Zijlstra <peterz at infradead.org> wrote: > On Fri, Oct 21, 2016 at 01:58:55PM +0200, Christian Borntraeger wrote: > > stop_machine can take a very long time if the hypervisor does > > overcommitment for guest CPUs. When waiting for "the one", lets > > give up our CPU by using the new cpu_relax_yield. > > This

On 10/22/2016 02:06 AM, Nicholas Piggin wrote: > On Fri, 21 Oct 2016 14:05:36 +0200 > Peter Zijlstra <peterz at infradead.org> wrote: > >> On Fri, Oct 21, 2016 at 01:58:55PM +0200, Christian Borntraeger wrote: >>> stop_machine can take a very long time if the hypervisor does >>> overcommitment for guest CPUs. When waiting for "the one", lets

A few days ago I uploaded to CRAN a new package called 'eha', which stands for 'Event History Analysis'. Its main focus is on proportional hazards modeling in survival analysis, and in that respect eha can be regarded as a complement and an extension to the 'survival' package. In fact eha requires survival. Eha contains three functions for proportional hazards

A few days ago I uploaded to CRAN a new package called 'eha', which stands for 'Event History Analysis'. Its main focus is on proportional hazards modeling in survival analysis, and in that respect eha can be regarded as a complement and an extension to the 'survival' package. In fact eha requires survival. Eha contains three functions for proportional hazards

To the R developers, The discussion below reminded me that I think it might be a good idea to take the Relevel function from the Lexis package and replace relevel in stats with it. This is really nothing special for epidemiology. It is fully compatible with the existing relevel (it actually contains the relevel code almost verbatim as a subset), but it has the extra functionality of combining

Danardono <daodao99 at student.umu.se> wrote: > > While waiting for 2.1, for those who need function[s] for this > survival-splitting business, as I do, this 'survcut' function below > might be helpful. > It is not an elegant nor efficient function but it works, at least for > some examples below. > Ditto the following, for the case where there are multiple

To Danardonos concern of splitting time for records with delayed entry: This can fairly easily be accomodated, by simply splitting time in small intervals of time since entry into the study, and then compute the value of the other timescales for each of these e.g.: current.age <- time.from.entry + age.at.entry but the cut on the other timescales will not be exactly where you may want them

I run Windows XP. and in a command window I get: > c:\stat\r\R-2.13.1\bin\i386\Rcmd Sweave Lexis.rnw Error in length(arg) : 'arg' is missing Calls: <Anonymous> Execution halted AND: > c:\stat\r\R-2.13.1\bin\i386\Rcmd Sweave --help Error in length(arg) : 'arg' is missing Calls: <Anonymous> Execution halted BUT: > c:\stat\r\R-2.13.0\bin\i386\Rcmd Sweave

I am trying to run PCA on a matrix (the first column and row are headers). There are several cells with NA's. When I run PCA with the following code: ______________________________________ setwd("I:/PCA") AsianProp<-read.csv("Matrix.csv", sep=",", header=T, row.names=1) attach(AsianProp) AsianProp AsianProp.pca<-princomp(AsianProp, na.omit)

Hi Folks, Apologies to anyone who'd prefer not to see this query on this list; but I'm asking because it is probably the forum where I'm most likely to get a good answer! I'm interested in the provenance of the name "normal distribution" (for what I'd really prefer to call the "Gaussian" distribution). According to Wikipedia, "The name "normal

Dear all, in order to estimate transition-specific probabilities in a multi-state model i applied the 'probtrans()' function from the 'mstate'-package. Now, i am at loss with the following message (see attached example): Warning message: In probtrans(msf.0, predt = 0) : Negative diagonal elements of (I+dA); the estimate may not be meaningful. I am not very familiar with matrix