search for: icc

...s: [\\NTSERVER\print$\W32X86\2\CNNSCORE.DLL] Dependentfiles: [\\NTSERVER\print$\W32X86\2\CNPXCMKM.DLL] Dependentfiles: [\\NTSERVER\print$\W32X86\2\CMDFPXK.DAT] Dependentfiles: [\\NTSERVER\print$\W32X86\2\CANLKN.PRF] Dependentfiles: [\\NTSERVER\print$\W32X86\2\CNZN15N.ICC] Dependentfiles: [\\NTSERVER\print$\W32X86\2\CNZN18N.ICC] Dependentfiles: [\\NTSERVER\print$\W32X86\2\CNZN21N.ICC] Dependentfiles: [\\NTSERVER\print$\W32X86\2\CNZE15N.ICC] Dependentfiles: [\\NTSERVER\print$\W32X86\2\CNZE18N.ICC] Dependentfiles: [\\NTSERVER\pr...

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: result<-icc(cbind(combatexpdata_p[1:62],combatexpd...

...3, evalR4, scoreR1, scoreR2, scoreR3, scoreR4, opinionR1, opinionR2, opinionR3, opinionR4. (there are more variables, but this gives an idea of the data structure). What I want is run several analyses on all 3 or 4-combinations of a given variable. So, for example, I want to compute the following ICC's (function from the psych package): ICC(cbind(evalR1,evalR2, evalR3)) ICC(cbind(evalR1,evalR2, evalR4)) ICC(cbind(evalR1, evalR3, evalR4)) ICC(cbind(evalR2, evalR3, evalR4)) ICC(cbind(evalR1, evalR2, evalR3, eval4)). I create a matrix containing the 3-combinations by combn(4,3). Now I need to...

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 function from the psych package. However, one of the datasets has varying numbers of judges for each group. One group may be rated by 2 judges, whereas others ma...

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/(bet...

Hello everyone. As some of you know, I was able to compile wine with Intel C++ Compiler (ICC), compilation log is located here: http://wine.x.pl/wine-1.1.38-ICC-compilation.log.tar.gz Some tests failed, and dxgi failed to compile (this is only related to DX10 I think), anyway all apps I tested worked fine (Red Faction 1 & 2, 3DMark 2000,2001SE,2003,Foobar2000,Operation Flashpoint), s...

...OK.DLL:OP51ENU.HLP:\ OKI HiperC Language Monitor:RAW:ABEXPW32.DLL,CANLKN.PRF,CNNbapie.DLL,\ CNNsCore.DLL,CNPPDCE.DLL,CNXADR.DLL,CNXCOV1.EMF,CNXCOV2.EMF,\ CNXCOV3.EMF,CNXCOVL.EMF,CNXCR.DLL,CNXDMAN.DLL,CNXECR.DLL,CNXP5EE.DLL,\ CNXP5EE0.CNT,CNXP5EE0.HLP,CNXP5EEP.DLL,CNXP5EEU.DLL,CNXPRASX.DLL,\ CNZ005N.ICC,CNZ006N.ICC,CNZ007N.ICC,CNZE15N.ICC,CNZE18N.ICC,\ CNZE21N.ICC,CNZN15N.ICC,CNZN18N.ICC,CNZN21N.ICC,CNZP15N.ICC,\ CNZP18N.ICC,CNZP21N.ICC,CnP5eE.DLL,CnP5eE0.CNT,CnP5eE0.HLP,\ CnP5eEUI.DLL,CnP5eEUM.DLL,DCS.DLL,DCSTBL.DLL,GP300FK.XPD,GP300PK.XPD,\ IMF32.DLL,IMFPRINT.DLL,ML51NSAR.DLL,OK001U2H.CAP,OK009U...

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...

..., I wanted to have a tool to compare LLVM against other compilers, so I wrote a little python program (attached) that filled my need. It is completely outside of the LLVM makefile framework, but this stems from the fact that I can use it to compare any GCC-like compiler, e.g. gcc-4.2 against Intel ICC. It also allows one to compare the generated code sizes, which can be quite nice. Here is a sample output of a boring run on hello programs: $ ./ccbench -v Checking compilers ... Compiler /usr/bin/g++-3.3 not found g++-4.1: g++-4.1 (GCC) 4.1.3 20070812 (prerelease) (Debian 4.1.2-15) g++-...

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...

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...

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) Variance StdDev (Intercept) 0.1829931 0...

I suspect that this is because the mask in your example is the result of a variable shift, which (a) has it’s own performance and flags hazards pre-SHLX and (b) requires additional µops to do with TEST. I expect that ICC is putting a dummy TEST or XOR ahead of the BT to break the false flags dependency, as well. If the mask were constant, I expect ICC would generate TEST instead (but I don’t have it handy to check). – Steve > On Jan 23, 2015, at 11:32 AM, Sanjay Patel <spatel at rotateright.com> wrote:...

Dear LLVM Community, I am D Tharun Kumar, masters student at Indian Institute of Technology Hyderabad, working in a team to improve current vectorizer in LLVM. As an initial study, we are studying various benchmarks to analyze and compare vectorizing capabilities of LLVM, GCC and ICC. We found that vectorization remarks given by LLVM are vague and brief, comparatively GCC and ICC are giving detailed diagnostics. - I am interested to know why the LLVM diagnostics are brief and not intuitive (making them less helpful)? - In our analysis we never seen llvm trying to v...

...d.grid(w=v1,x=v1,y=v1,z=v1) >n<-dim(eval)[1] > >results<-rep("", n) > >for (i in 1:n) { > row<-unique(unlist(eval[i,])) > > if (length(row)>=3) results[i]<-testfun(row) >} > >You just have to replace testfun by your own function in this case ICC. > >Sincerly... > > >Justin BEM >BP 1917 Yaoundé >Tél (237) 76043774 > > > > > > >De : Helter Two <heltertwo@care2.com> >À : r-help@r-project.org >Envoyé le : Lundi, 7 Septembre 2009, 18h17mn 22s >Objet : [R] calling combinations of variable...

On Tue, Sep 8, 2015 at 7:36 PM, Tom Callaway <tcallawa at redhat.com> wrote: > On 09/07/2015 06:16 AM, arnaud gaboury wrote: >> I want to create a clean .rpm package for R built with MKL and ICC. I >> follow Fedora instrcutions[0] to create the package. As a base, I use >> the R-3.2.2.src.rpm. >> >> I am left with this error: >> >> ------------------------------------------ >> installing R info pages ... >> updating '/usr/share/info/dir...

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 the Intel compilers are...

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" CXX=icpc CXXFLAGS="-g -O3" FC=ifort FCFLAGS="-g -O3 -mp" in my config.sit...

...t the "-host" option indicating a cross compilation. Intel suggests to use "x86_64-unknown-linux-gnu". However, either using "x86_64-unknown-linux-gnu" or something unknown like "unknown" brings me through the configuration: ../llvm/configure CXX=icpc CC=icc CXXFLAGS="-O3 -mmic" CFLAGS="-O3 -mmic" --host=x86_64-unknown-linux-gnu configure: WARNING: If you wanted to set the --build type, don't use --host. If a cross compiler is detected then cross compile mode will be used. checking for x86_64-unknown-linux-gnu-clang... ic...

Hello R users, and perhaps William Revelle in particular, I'm curious as to how ICC deals with missing data, so for example you are sampling individuals over set periods in time and one individual is missing or was not recaptured at that given time point - leading to NA in the dataset. My thought was that it should then omit data by individual, but I'm not convinced that that...