search for: iccs

Hello, I have problems setting up a canon multifunction ir7200. When I print the windows test page, I have something like "smiley" "arrow" "arow" "smiley" "arrow" name_of_the_samba_spool "smileys" driver.dll etc,etc,etc, on a single line. Did somebody used such a multifunction with Samba ? Below is a (long) description of what I did. I

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:

R-2.9.1, Windows7 Dear list, I have a question to you that seems very simple to me, but I just can't figure it out. I have a dataframe called "ratings" which contains the following variables: evalR1, evalR2, evalR3, evalR4, scoreR1, scoreR2, scoreR3, scoreR4, opinionR1, opinionR2, opinionR3, opinionR4. (there are more variables, but this gives an idea of the data structure). What

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

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

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), so I did

Hi, I'm trying to add a Windows NT/2000 OKI C5100 print driver to a Samba 2.2.3a server. I've been told that this driver does some server-side stuff, so I'll have to use 'adddriver' in rpcclient. I've read the manual page for rpcclient, and I printed out a 'Windows 2000 Printer Test Page' to get all the relevant information. This is probably just something

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

Hi All ! Recently in the mailing list there was the question about benchmarking LLVM. I was told that LLVM get's benchmarked in the nightly test. While this is true, 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

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,

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

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)

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

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

Thanks to Justin, Baptiste, and Sebed for your answers. The solutions work well. I have been putting them to good use today: the code now works wonderfully and I learnt some useful tricks! thanks, Peter <-----Original Message-----> >From: justin bem [justin_bem@yahoo.fr] >Sent: 9/8/2009 9:06:23 AM >To: heltertwo@care2.com >Cc: r-help@stat.math.ethz.ch >Subject: Re: Re :

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: >> >>

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 stricter and give more precise warnings than gcc.

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 am trying to build LLVM 3.4 RC1 with the Intel compiler targeting the Xeon Phi (native). In order to skip the building and execution of a test binary during configuration one needs the set 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

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 is what it