search for: 21.02

Hi >i have this data > X [1] 5.79 1579.52 2323.70 68.85 426.07 110.29 108.29 1067.60 17.05 22.66 [11] 21.02 175.88 139.07 144.12 20.46 43.40 194.90 47.30 7.74 0.40 [21] 82.85 9.88 89.29 215.10 1.75 0.79 15.93 3.91 0.27 0.69 [31] 100.58 27.80 13.95 53.24 0.96 4.15 0.19 0.78 8.01 31.75 [41] 7.35 6.50

I have Data like this: Tone OQtil4 OQ0 GOtil4 GO0 SKrhsJ SK0 RCrhsJ RC0 1 HsLG -9.1347877 -2.97 -7.409590 -6.40 9.389357 20.60 10.688854 24.40 2 HsLG -7.9270569 -2.03 -7.861541 -6.90 10.165324 26.40 10.640183 23.10 3 HsLG -7.0394106 -1.26 -7.509566 -6.53 12.033194 30.87 9.401959 20.37 4 HsLG -6.8625610 -1.03 -7.645118 -6.68 10.372605 24.22 9.378803 17.82 5

Dear R-helpers, I tried the playwith packages for the first time, and it crashed R: > require(playwith) Loading required package: playwith Loading required package: lattice Loading required package: grid Loading required package: gWidgets Loading required package: gWidgetsRGtk2 Loading required package: RGtk2 Loading required package: cairoDevice > sessionInfo() R version 2.7.1

Duncan, Below are the tabulated compile times and executable sizes. A) gcc 4.5.4svn using -msse3 -ffast-math -O3 -fno-tree-vectorize B) gcc 4.5.4svn/dragonegg using -msse3 -ffast-math -O3 -fno-tree-vectorize -fplugin-arg-dragonegg-enable-gcc-optzns C) gcc 4.5.4svn/dragonegg using -msse3 -ffast-math -O3 -fno-tree-vectorize Compile time (seconds) Benchmark A) stock B) gcc 4.5.4/ C)

Hi Jack, thanks for doing this. > Below are the tabulated compile times and executable sizes. > > A) gcc 4.5.4svn using -msse3 -ffast-math -O3 -fno-tree-vectorize > B) gcc 4.5.4svn/dragonegg using -msse3 -ffast-math -O3 -fno-tree-vectorize -fplugin-arg-dragonegg-enable-gcc-optzns > C) gcc 4.5.4svn/dragonegg using -msse3 -ffast-math -O3 -fno-tree-vectorize These numbers really

Back a year ago, I asked what the key DC executables where that I had to bring from my compile host to the production imap server to install or upgrade DC. I was told: dovecot, dovecot.conf, dovecot-auth, imap & imap-login I recently got DC up and running unencrypted and that worked fine. Then I tried to enable SSL and the logs said I was missing

-----Messaggio originale----- Da: Michael Camann <camann at babylon.cnrs.humboldt.edu> A: r-help at stat.math.ethz.ch <r-help at stat.math.ethz.ch> Data: marted? 22 agosto 2000 21.02 Oggetto: [R] various ordinations >Colleagues, > >I'm developing a library of functions for community ecology analyses and >have a couple of questions that I've not been able to answer

I just discovered that dovecot supports copying messages via hard-linking. I have a huge mailbox hierarchy of existing messages that I'd prefer to store that way. Is there a simple way to transform non-hard-linked storage to hard-linked? TIA, -- Dave Abrahams Meet me at BoostCon: http://www.boostcon.com BoostPro Computing http://www.boostpro.com

This doesn't seem to affect clients, but I'm seeing an occasional pop3 error in the log over the last week. Any ideas what is causing this? Thanks, Ken > Jul 4 15:04:03 mail dovecot: POP3(user)x.x.x.x: Connection > closed top=0/0, retr=0/0, del=0/4582, size=246709805 > Jul 4 15:04:03 mail dovecot: POP3(user)x.x.x.x: Panic: file > pop3-client.c: line 585

Dear List, i am trying to produce a 3d plot using wireframe using the code: wireframe(Residuals_FD ~ Elevation * Temperature, data = data2, scales = list(arrows = FALSE), drape = TRUE, colorkey = TRUE) As you can see when the code (using the data below) is run the plot area is set-up correctly but the actual surface is missing? Any help would be greatly appreciated. Chris #data Elevation

Hi. I have 2 tables, with same dimensions (8000 x 5). Something like: tab1: V1 V2 V3 V4 V5 14.23 1.71 2.43 15.6 127 13.20 1.78 2.14 11.2 100 13.16 2.36 2.67 18.6 101 14.37 1.95 2.50 16.8 113 13.24 2.59 2.87 21.0 118 tab2: V1 V2 V3 V4 V5 1.23 1.1 2.3 1.6 17 1.20 1.8 2.4 1.2 10 1.16 2.6 2.7 1.6 11 1.37 1.5 2.0 1.8 13 1.24 2.9 2.7 2.0 18 I need generate a table of averages, the

I just installed CentOS-5 but when I try to update I get this: # yum clean all Loading "installonlyn" plugin Cleaning up Everything [root at inet02 ~]# yum update Loading "installonlyn" plugin Setting up Update Process Setting up repositories base 100% |=========================| 1.1 kB 00:00 updates 100% |=========================|

Hi Jack, thanks for these numbers. Can you also please measure compile times? I'm thinking of enabling gcc optimizations by default, but I don't want to increase compile times, which means choosing a value for the -fplugin-arg-dragonegg-llvm-ir-optimize option that is low enough to get good compile times, yet high enough to get fast code. It would be great if you could play around with

On Thu, Jun 09, 2011 at 03:44:40PM +0200, Duncan Sands wrote: > Hi Jack, thanks for doing this. > >> Below are the tabulated compile times and executable sizes. >> >> A) gcc 4.5.4svn using -msse3 -ffast-math -O3 -fno-tree-vectorize >> B) gcc 4.5.4svn/dragonegg using -msse3 -ffast-math -O3 -fno-tree-vectorize -fplugin-arg-dragonegg-enable-gcc-optzns >> C)

Hi R Users, I am going to run a multiple linear regression with around 57 independent variables. Each time I run the model with just 11 variables, the results are reasonable. With increasing the number of independent variables more than 11, the coefficients will get ?NA? in the output. Is there any limitation for the number of independent variables in multiple linear regressions in R? I attached

Current dragonegg svn has all of the -fplugin-arg-dragonegg-enable-gcc-optzns bugs for usage with -ffast-math -O3 addressed except for those related to PR2314. Using the -fno-tree-vectorize option, we can evaluate the current state of -fplugin-arg-dragonegg-enable-gcc-optzns with the Polyhedron 2005 benchmarks compared to stock dragonegg and stock gcc 4.5.4. The runtime benchmarks below show that

Dear R Helpers, A few weeks ago I asked for some help on how to accomplish modifications to data in a set of data frames. As part of that request I mentioned that I realized that one way to accomplish my goal was to put the data frames together in a list but that I was looking for a way to do it with data frames and a loop because I "believe the better thing is to work df by df for my

R Help - I'm trying to run a correlation matrix with a covariate of "age" and will at some point will also want to covary other variables concurrently. I'm using the "psych" package and have tried other methods such as writing a loop to extract semi-partial correlations, but it does not seem to be working. How can I accomplish this? library(psych) > set.cor(y =

On Thu, Jun 09, 2011 at 03:44:40PM +0200, Duncan Sands wrote: > Hi Jack, thanks for doing this. > >> Below are the tabulated compile times and executable sizes. >> >> A) gcc 4.5.4svn using -msse3 -ffast-math -O3 -fno-tree-vectorize >> B) gcc 4.5.4svn/dragonegg using -msse3 -ffast-math -O3 -fno-tree-vectorize -fplugin-arg-dragonegg-enable-gcc-optzns >> C)

Hello R users, For the last few days I am struggling with the following task: my data.frame: A1 A2 A3 B1 B2 B3 58.81 53.292 54.501 13.013 17.39 19.407 56.02 56.251 54.033 20.099 13.15 10.411 55.376 53.099 57.625 13.396 21.031 13.22 58.584 53.194 54.218 13.038 16.854 19.289 55.7 55.921 53.847 19.942 13.153 9.828 55.093 52.934