similar to: [LLVMdev] x86_64-apple-darwin Polyhedron 2005 benchmarks

I am finding with the patch that all of the Polyhedron 2005 benchmarks pass on i686-apple-darwin9. Could someone clarify the regression rules for releases? Not building a secondary language on a primary target is usually considered a P1 regression for FSF gcc. Not doing so here gives one the impression that llvm.org isn't playing by the same rules. No one is ever going to want to use these

The previously posted benchnarks for gcc vs llvm-gfortran had one mistake. I was actually had the gfortran for 4.3.1 installed instead of that from gcc 4.2.4. Below are the polyhedron benchmark results for all three compilers... gfortran 4.2.4 Benchmark Compile Executable Ave Run Number Estim Name (secs) (bytes) (secs) Repeats Err % --------- -------

Hello, I am using package MuMIn to calculate AIC for a full model with 10 explanatory variables. Thanks in advance in sharing your experience. Q1 In the AIC list of all models, each model is differentiated by model number. Please kindly advise if it is possible to find the corresponding explanatory variable(s) for the model number. Q2 error message I tried to display sub-model with only

Estimados Este es el test de friedman que se logra asi library(PMCMR) y <- matrix(c( 3.88, 5.64, 5.76, 4.25, 5.91, 4.33, 30.58, 30.14, 16.92, 23.19, 26.74, 10.91, 25.24, 33.52, 25.45, 18.85, 20.45, 26.67, 4.44, 7.94, 4.04, 4.4, 4.23, 4.36, 29.41, 30.72, 32.92, 28.23, 23.35, 12, 38.87, 33.12, 39.15, 28.06, 38.23, 26.65),nrow=6, ncol=6, dimnames=list(1:6,LETTERS[1:6])) print(y)

Dear Rusers, I have met a difficult problem on explaining the differences of principal component analysis(PCA) between R,S-PLUS and SAS/STATA/SPSS, which wasn't met before. Althought they have got the same eigenvalues, their coeffiecients were different. First, I list my results from R,S-PLUS and SAS/STATA/SPSS, and then show the original dataset, hoping sb. to try and explain it.

Hello, This is a standard example in which I read the time series data from a csv file and create a zoo object: x0 <- read.csv(file="CPI.csv", header=TRUE) time_0<-as.yearmon("1981-01")+(0:371)/12 x0zoo<-zoo(x0, time_0) The data look like this: TIME CPI CPI_food CPI_Clothes CPI_House CPI_Rent 198101 62.1 55.34 103.45 65.24 61.43 198102 63.16 56.95

All, I would like to apply a set of rules to each row of the sample data set below. The rule sets are the guidelines for determining an individual's date for retirement eligibility. The rules are found in this document, http://www.opm.gov/feddata/RetirementPaperFinal_v4.pdf. I am only interested in the top two categories for retirement eligibility, the CSRS and FERS plans. The data set has

Taking the Grunfeld data, which is built-in in R, for example, (1)How can I construct a dataset (or dataframe) that consists of the data of all firms in 1951? (2)How can I calculate the average capital in each form over the period 1951-1954? What I can imagine is to categorize the data by firm, and then select the data between 1951 and 1954 for each firm, but how can I do it? Thanks, Miao

Forum, Using the following data: DF<-read.table(textConnection("A B 22.60 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA 102.00 NA 19.20 NA 19.20 NA NA NA NA NA NA NA 11.80 NA 7.62 NA NA NA NA NA NA NA NA NA NA NA 75.00 NA NA NA 18.30 18.2 NA NA NA NA 8.44 NA 18.00 NA NA NA 12.90 NA"),header=T) closeAllConnections() The second column is a duplicate

All, I've read several tutorials re: generating wireframes, but am clearly missing something. I have data along the lines of: > tbl [1:10,] Visits Activity Course.Grade 1 17 2 18.31 2 7 11 20.67 3 9 17 24.69 4 28 71 38.72 5 43 107 45.46 6 14 5 47.77 7 25 51

Hi, Today I came accros a very interesting thing. I was asked how much time it takes for R to calculate the product of two large matrices. So I generated two 2000x2000 matrices of random normal numbers and measured the time with function system.time m1 <- matrix(rnorm(2000*2000),2000) m2 <- matrix(rnorm(2000*2000),2000) system.time(m3 <- m1%*%m2) and it produced 46.47 0.36 47.68

Hi, I have a dataset of historical monthly temperature data that is grouped by weather station. I want to create z-scores of the monthly data using a base period of a subset of years. I subset the dataset first to include only data from the years (V2) that make up the base period so I could calculate the appropriate means and standard deviations V1 V2 V3 V12 V15 V16 V19 84

Hello all again, I want to do bitwise addition in R. I am trying to generate a matrix 0000 0001 0010 .... .... 1111 I know the other ways of generating this matrix but I need to look at bitwise addition. Any suggestions??? thanks a lot Nameeta ------------------------------------------------- This email is intended only for the use of the individual or...{{dropped}}

Issue: Vista reads slowly from a samba server. This appears to pop up periodically here and elsewhere. My samba.conf file has: [homes] ... vfs objects = readahead As suggested elsewhere. Writes are approximately 17-18MB/s which is acceptable. Reads are in the 8MB/s range which is appalingly slow. Using linux smbclient and windows XP clients I can read at 25+MB/s. I've enabled vfs

On Sat, 2011-10-29 at 14:02 -0500, Hal Finkel wrote: > On Sat, 2011-10-29 at 12:30 -0500, Hal Finkel wrote: > > Ralf, et al., > > > > Attached is the latest version of my autovectorization patch. llvmdev > > has been CC'd (as had been suggested to me); this e-mail contains > > additional benchmark results. > > > > First, these are preliminary

Duncan, Here are the complete benchmarks rerun against gcc 4.5.4 built with... Using built-in specs. COLLECT_GCC=gfortran-fsf-4.5 COLLECT_LTO_WRAPPER=/sw/lib/gcc4.5/libexec/gcc/x86_64-apple-darwin11.0.0/4.5.4/lto-wrapper Target: x86_64-apple-darwin11.0.0 Configured with: ../gcc-4.5.4/configure --prefix=/sw --prefix=/sw/lib/gcc4.5 --mandir=/sw/share/man --infodir=/sw/lib/gcc4.5/info

On Sat, 2011-10-29 at 15:16 -0500, Hal Finkel wrote: > On Sat, 2011-10-29 at 14:02 -0500, Hal Finkel wrote: > > On Sat, 2011-10-29 at 12:30 -0500, Hal Finkel wrote: > > > Ralf, et al., > > > > > > Attached is the latest version of my autovectorization patch. llvmdev > > > has been CC'd (as had been suggested to me); this e-mail contains > >

Dear R users, I have two data frames that consist of statistical information for most countries around the world. One dataframe consists of the latitude and longitude ("coord.csv") of each country, while the other consists of 100's of different attributes ("countryattri.csv") for each country (like, GDP, Population, etc.). The data is organized with a header and then

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)

Dear all, I want to do a F test, which involves calculation of the degrees of freedom for the residuals. Now say, I have a nlme object "mod.nlme". I have two questions 1.How do I extract the degrees of freedom? 2.How is this degrees of freedom calculated in an nlme model? Thanks. Jun Shen Some sample code and data =================================================================