search for: 0.1000

Hi guys, I'm trying to use lmomco package. first I did the manual calculation on what is the estimates scale and location parameter given L-CV=0.2, L1=1000 L-moments and k (shape parameter) =- 0.1. so what i get is: location: 821.0445 scale: 260.7590 shape: -0.1000 #I assign this as GEV vectors using vec2par GEVpara2<-vec2par(c( 821.0445 , 260.7590 ,-0.1),'gev') #then I

I just upgraded our optimizer to LLVM 3.0 from 2.8 and noticed that the scalar replacement of aggregates pass takes a lot longer for some code. Has there been a performance regression in this pass, or does it do more work? LLVM 3.0: Total Execution Time: 1.0600 seconds (1.0526 wall clock) ---User Time--- --System Time-- --User+System-- ---Wall Time--- --- Name --- 0.5100

Hello, My name is Craig and I need help plotting a "line" for a multiple linear regression in R. Here is my sample data (filename: convis.txt) Output of convis.txt is (vis and density being predictors of either avoidance or entrance): vis den avoid entrance 1 10 1 0.0000 0.0000 2 10 3 0.8750 0.0000 3 8 3 0.8180 0.0300 4 8 3 0.6670 0.0667 5 8 1

Hello all, Consider the following problem: There is a matrix of probabilities: > set.seed(1) > probs <- array(abs(rnorm(25, sd = 0.33)), dim = c(5,5), dimnames = list(1:5, letters[1:5])) > probs a b c d e 1 0.21 0.27 0.50 0.0148 0.303 2 0.06 0.16 0.13 0.0053 0.258 3 0.28 0.24 0.21 0.3115 0.025 4 0.53 0.19 0.73 0.2710 0.656 5 0.11 0.10 0.37 0.1960

f <- (structure(list(X = structure(96:97, .Label = c("119DAmm", "119DN", "119DNN", "119DO", "119DOC", "119Flow", "119Nit", "119ON", "119OPhos", "119OrgP", "119Phos", "119TKN", "119TOC", "148DAmm", "148DN", "148DNN", "148DO",

Hello again! Is there a way to include a mean in the garch function in the library(tseries), please? I tried include.mean=T in the function statement but it didn't work thanks in advance! R Version 2.2.1 Windows Sincerely, Erin mailto: hodgess at gator.uhd.edu

Hello, I am attempting to train a random forest model using the randomForest package on 500,000 rows and 8 columns (7 predictors, 1 response). The data set is the first block of data from the UCI Machine Learning Repo dataset "Record Linkage Comparison Patterns" with the slight modification that I dropped two columns with lots of NA's and I used knn imputation to fill in other gaps.

Hi, LLVM 2.1-pre1 test results: Linux (SUSE) on x86 (P4) Release mode, but with assertions enabled LLVM srcdir == objdir # of expected passes 2250 # of expected failures 5 I ran the llvm-test suite on my desktop while I was also working on that PC, so don't put too much trust in the timing info. Especially during the "spiff" test the machine was swapping

Hi all, I have a package that is specific to a task I was repetitively using a few years ago. I now needed to run it again with new data. However I am told it was built with an older version or R and will not work. How can I tweak the package so it will run on 11.1? It was a one-off product and has not been maintained. Is there a way to "unpackage" it and repackage it to work? I

G'Day Tanya, Is it too late to bring in the following patches to fix some major brokenness in the AuroraUX tool chain for 2.6? http://llvm.org/viewvc/llvm-project/cfe/trunk/lib/Driver/Tools.cpp?r1=84468&r2=84469&view=diff&pathrev=84469 http://llvm.org/viewvc/llvm-project/cfe/trunk/lib/Driver/Tools.cpp?r1=84265&r2=84266&view=diff&pathrev=84266

Hi Tanya, > 1) Compile llvm from source and untar the llvm-test in the projects > directory (name it llvm-test or test-suite). Choose to use a > pre-compiled llvm-gcc or re-compile it yourself. I compiled llvm and llvm-gcc with separate objects directories. Platform is x86_64-linux-gnu. > 2) Run make check, report any failures (FAIL or unexpected pass). Note > that you need to

require(randomForest) rf.pred<-predict(fit, valid, type="prob") > rf.pred[1:20, ] 0 1 16 0.0000 1.0000 23 0.3158 0.6842 43 0.3030 0.6970 52 0.0886 0.9114 55 0.1216 0.8784 75 0.0920 0.9080 82 0.4332 0.5668 120 0.2302 0.7698 128 0.1336 0.8664 147 0.4272 0.5728 148 0.0490 0.9510 153 0.0556 0.9444 161 0.0760 0.9240 162 0.4564 0.5436 172 0.5148 0.4852 176 0.1730

On Oct 20, 2009, at 6:02 AM, Duncan Sands wrote: > Hi Tanya, > >> 1) Compile llvm from source and untar the llvm-test in the projects >> directory (name it llvm-test or test-suite). Choose to use a pre- >> compiled llvm-gcc or re-compile it yourself. > > I compiled llvm and llvm-gcc with separate objects directories. > Platform is x86_64-linux-gnu. > Ok.

On Sun, Jan 20, 2013 at 1:26 PM, Redmond, Paul <paul.redmond at intel.com> wrote: > There is almost certainly a bug in lnt or the makefiles. > > I changed the body of Burg main to the following: > > + printf("Hello World\n"); > + return 0; > > > I re-ran the test-suite again and got the following errors: > > --- Tested: 986 tests -- > FAIL:

LLVMers, 2.6 pre-release2 is ready to be tested by the community. http://llvm.org/prereleases/2.6/ If you have time, I'd appreciate anyone who can help test the release. To test llvm-gcc: 1) Compile llvm from source and untar the llvm-test in the projects directory (name it llvm-test or test-suite). Choose to use a pre- compiled llvm-gcc or re-compile it yourself. 2) Run make check,

There is almost certainly a bug in lnt or the makefiles. I changed the body of Burg main to the following: + printf("Hello World\n"); + return 0; I re-ran the test-suite again and got the following errors: --- Tested: 986 tests -- FAIL: MultiSource/Applications/Burg/burg.execution_time (494 of 986) FAIL: MultiSource/Applications/ClamAV/clamscan.execution_time (495 of 986) FAIL:

LLVMers, The 2.5 pre-release is available for testing: http://llvm.org/prereleases/2.5/ If you have time, I'd appreciate anyone who can help test the release. Please do the following: 1) Download/compile llvm source, and either compile llvm-gcc source or use llvm-gcc binary (please compile llvm-gcc with fortran if you can). 2) Run make check, send me the testrun.log 3) Run "make

Estimados Al dirigir la lectura de un folder tYA1.csv me da este error y no me percato del motivo, adjunto archivo. Espero su ayuda Saludos Jos? > setwd("D:/Public/Documents/R/bioimpedancia") > a<-read.csv("tYA1.csv",header=TRUE, sep=",", dec=".") Error in read.table(file = file, header = header, sep = sep, quote = quote, : more

Dear R users, I have a linear model of the kind outcome ~ treatment + covariate where 'treatment' is a factor with three levels ("0", "1", and "2"), and the covariate is continuous. Treatments "1" and "2" both have regression coefficients significantly different from 0 when using treatment contrasts with treatment "0" as the

LLVMers, The 2.1 pre-release (version 1) is available for testing: http://llvm.org/prereleases/2.1/version1/ I'm looking for members of the LLVM community to test the 2.1 release. There are 2 ways you can help: 1) Download llvm-2.1, llvm-test-2.1, and the appropriate llvm-gcc4.0 binary. Run "make check" and the full llvm-test suite (make TEST=nightly report). 2) Download