similar to: Wine, ICC compilation and performance tests.

The performance of WineD3D depends on the application and display drivers. It is hard to say where we are losing the performance and whether it is WineD3D which has to be blamed. To find out where the performance is lost you need to profile the app using e.g. sysprof or oprofile. Then you can see where the time is spent. Typically we don't spend a lot of time in Wine code but outside Wine in

Win7, R2.11.0 I am working on a report together with several co-authors. The data concern several performance measures on a set of groups. These measures are scored by external judges. We report findings on several datasets, including several of the 6 ICC's discussed by Shrout & Fleiss (1979). We determine these using the icc function from the irr package. We have also used the ICC

Is there a way to set registry key, other then editing system.reg/user.reg file? For DIB engine we can export WINEDIB=ON or edit registry, is this the case with other registry keys as well? Thanks in advance. -------------- next part -------------- An HTML attachment was scrubbed... URL: <http://www.winehq.org/pipermail/wine-users/attachments/20090524/b69fa546/attachment.htm>

Dear R users I would like to ask a question regarding to icc (intraclass correlation) or many biologists refer it to as repeatability. It is very useful to get icc for many reasons and it is easy to do so from linear mixed-effects models and many packages like psy, psychometric, aod and irr have functions to calculate icc. icc = between-group variance/(between-group variance + residual

I am helping someone calculate ICC using R. I know R has several packages like irr, psy etc which provide options to calculate ICC (intraclass correlation coefficient). When getting ICC, we need to use the model: two-way mixed model with absolute agreement. I only found that in irr package, it provides the option of choosing one or two way and consistence or absolute agreement model. However,

Hi, all There are 62 samples in my data and I tested 3 times for each one, then I want to use ICC(intraclass correlation) from irr package to test the consistency among the tests. *combatexpdata_p[1:62] is the first text results and combatexpdata_p[63:124] * is the second one and *combatexpdata_p[125:186]* is the third. Here is the result:

>>>>> CanisMaior writes: > Bugs compiling R-1.7.1 with Intel compilers icc and ifc, > on x86-computer (Pentium IV) and linux operating system > Hello, > as there aren't many reports about that issue, I'll give a little > report here. (Hope I don't bother anyone) > The best thing about using icc and ifc are the warnings, because > it is said that

I would appreciate some thoughts on using the bootstrap functions in the library "bootstrap" to estimate confidence intervals of ICC values calculated in lme. In lme, the ICC is calculated as tau/(tau+sigma-squared). So, for instance the ICC in the following example is 0.116: > tmod<-lme(CINISMO~1,random=~1|IDGRUP,data=TDAT) > VarCorr(tmod) IDGRUP = pdLogChol(1)

Dear developeRs, As of icc 10, the -c99 option is deprecated, and generates a lot of warnings when compiling R or R packages. If you use CC="icc -std=c99" instead of just CC="icc", R's configure will not add the -c99 option, and the code seems to compile and run just fine. (Please don't hesitate to let me know if this is a bad idea. :-) -- Regards, Bj?rn-Helge

Hello again. Can somebody please tell me what does ?CC?/?Default CC? in bug report form means? What should we write there? Thanks -------------- next part -------------- An HTML attachment was scrubbed... URL: <http://www.winehq.org/pipermail/wine-users/attachments/20090503/649746c6/attachment.htm>

Hello, R-folks: Here is a statement I use to make a data frame: iccdata <- data.frame(i=rep(1:10,rep(2,10)),j=rep(1:2,10), x=c(0.35011,0.11989,0.13081,0.09919,0.16000,0.12000,0.00000,0.00000, 0.44023,0.32977,2.67081,2.63919,0.09050,0.03950,0.44019,0.30981,0.59000, 0.57000,4.03000,3.77000)) Then here are the data: > iccdata i j x 1 1 1 0.35011 2 1 2 0.11989 3 2 1 0.13081 4

On Fri, Sep 4, 2015 at 5:58 PM, Martyn Plummer <plummerm at iarc.fr> wrote: > On Wed, 2015-09-02 at 20:49 +0200, arnaud gaboury wrote: >> On Wed, Sep 2, 2015 at 7:35 PM, arnaud gaboury <arnaud.gaboury at gmail.com> wrote: >> > After a few days of reading and headache, I finally gave a try at >> > building R from source with Intel MKL and ICC. Documentation

So far, i couldn't find an answer on the net, maybe someone here can help me: Is it possible to install ICC-profiles under WINE? If yes, how can this be done? (I need support of ICC-profiles, because i run PhotoLine under WINE) Any help would be very much appreciated! Michael

Hi, I'm essentially wanting to calculate intra- and inter-observer variabilities for the first principal component of an optic disc shape measure of a sample of individuals, so from what I can work out I need to work out an intraclass correlation coefficient(s). For the intra-data, I have 2 measurements taken on each individual by the same observer. For the inter-data, 2 observers have taken

https://bugs.freedesktop.org/show_bug.cgi?id=111178 Bug ID: 111178 Summary: low quality icc profile for monitor Benq ew2775zh Product: xorg Version: unspecified Hardware: x86-64 (AMD64) OS: Linux (All) Status: NEW Severity: normal Priority: medium Component: Driver/nouveau

arnaud gaboury <arnaud.gaboury at gmail.com> writes: > After a few days of reading and headache, I finally gave a try at > building R from source with Intel MKL and ICC. Documentation and posts > on this topic are rather incomplete, sometime fantasist et do not give > much explanations about configure options. > As I am not sure if mine is correct, I would appreciate some

On Fri, Sep 4, 2015, 9:24 AM Bj?rn-Helge Mevik <b.h.mevik at usit.uio.no> wrote: arnaud gaboury <arnaud.gaboury at gmail.com> writes: > After a few days of reading and headache, I finally gave a try at > building R from source with Intel MKL and ICC. Documentation and posts > on this topic are rather incomplete, sometime fantasist et do not give > much explanations about

Hi Arnaud -- I'm glad it's working for you. I'm not sure I understand your final answer. Are you saying that the version I posted worked for you as given, or that you had to remove some of the other options? Perhaps you could post the full final recipe in a way that others can copy and paste if they find this thread in the future? Also, did you determine if the the same approach

I am having trouble compiling R-2.6.2 on suse linux x86_64 using the intel compiler. I read section C.2.1 Intel compilers in the R Installation and Administration manual, and put CC=icc CFLAGS="-g -O3 -wd188 -ip" F77=ifort FFLAGS="-g -O3" ICC_LIBS=/opt/intel/cce/10.1.012/lib IFC_LIBS=/opt/intel/fce/10.1.012/lib/ LDFLAGS="-L$ICC_LIBS -L$IFC_LIBS -L/usr/lib64"

Hi, I'm trying to run a ICC calculation on a data frame. I get the following error message: Error in data.frame(x.s, subs = rep(paste("S", 1:n.obs, sep = ""), nj)) : arguments imply differing number of rows: 1700, 1750 I've looked at the data in the file and it seems to be okay. Any thoughts would be much appreciated. I'm getting used to R so if possible, I