similar to: clarificatin on validate.ols method='cross'

Hi everyone,   I'm trying to do an Logistic Politomic Regression in R. Because I have my resposes variables and the aswer is 0 and 1 in 3 bacterial genes. Somebody know how to do this in R in a easy way?   Thank so much,   José Bustos Facultad de Ciencias Universidad Catolica Ssma. Concepcion Chile --- El lun, 31/8/09, r-help-request@r-project.org <r-help-request@r-project..org>

Dear R-Help I am running apply on a data.frame containing factors and numeric columns. It appears to convert are columns into as.character? Does it convert data.frame into matrix? Is this expected? I wish it to recognise numerical columns and round numbers. Can I use another function instead of apply, or should I use a for loop in the case? > summary(xmat) A B

I have two assignment problems... I have written this small code for regression with two regressors . n <- 50 x1 <- runif(n,1,10) x2 <- x1 + rnorm(n,0,0.5) plot(x1,x2) # x1 and x2 strongly correlated cor(x1,x2) y <- 3 + 0.5*x1 + 1.1*x2 + rnorm(n,0,2) intact.lm <- lm(y ~ x1 + x2) summary(intact.lm) anova(intact.lm) the questions are 1.The function summary() is convenient since

I have two assignment problems... I have written this small code for regression with two regressors . n <- 50 x1 <- runif(n,1,10) x2 <- x1 + rnorm(n,0,0.5) plot(x1,x2) # x1 and x2 strongly correlated cor(x1,x2) y <- 3 + 0.5*x1 + 1.1*x2 + rnorm(n,0,2) intact.lm <- lm(y ~ x1 + x2) summary(intact.lm) anova(intact.lm) the questions are 1.The function summary() is convenient since

Hello, I?m using zero-inflated Poisson regression via the zeroinfl() function to analyze data on seed-set of plants, but for some reason, I don?t seem to be getting the output for all three levels of my two categorical predictors. More about my data and model: My response variable is the number of viable seeds (AVInt), and my two categorical predictors are elevation (Elev) and Treatment

Dear all, I'm using R 2.8.1 under Windows Vista on a dual core 2,4 GhZ with 4 GB of RAM. I'm trying to reproduce a result out of "Analysis of Financial Time Series" by Ruey Tsay. In R I'm using the fGarch library. After fitting a ar(3)-garch(1,1)-model > model<-garchFit(~arma(3,0)+garch(1,1), analyse) I'm saving the results via > result<-model

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

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

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

On 09/09/2013 05:18 AM, Star Tan wrote: > > At 2013-09-09 05:52:35,"Tobias Grosser" <tobias at grosser.es> wrote: > >> On 09/08/2013 08:03 PM, Star Tan wrote: >> Also, I wonder if your runs include the dependence analysis. If this is >> the case, the numbers are very good. Otherwise, 30% overhead seems still >> to be a little bit much. > I think

At 2013-09-09 13:07:07,"Tobias Grosser" <tobias at grosser.es> wrote: >On 09/09/2013 05:18 AM, Star Tan wrote: >> >> At 2013-09-09 05:52:35,"Tobias Grosser" <tobias at grosser.es> wrote: >> >>> On 09/08/2013 08:03 PM, Star Tan wrote: >>> Also, I wonder if your runs include the dependence analysis. If this is >>> the

At 2013-09-09 05:52:35,"Tobias Grosser" <tobias at grosser.es> wrote: >On 09/08/2013 08:03 PM, Star Tan wrote: >> Hello all, >> >> >> I have done some basic experiments about Polly canonicalization passes and I found the SCEV canonicalization has significant impact on both compile-time and execution-time performance. > >Interesting. > >>

Hello all, I have evaluated the compile-time and execution-time performance of Polly canonicalization passes. Details can be referred to http://188.40.87.11:8000/db_default/v4/nts/recent_activity. There are four runs: pollyBasic (run 45): clang -O3 -Xclang -load -Xclang LLVMPolly.so pollyNoGenSCEV (run 44): clang -O3 -Xclang -load -Xclang LLVMPolly.so -mllvm -polly -mllvm -polly-codegen-scev

I might be sorry for asking this question :-) I have two equations and I tried to estimate them individually with "lm" and "gls", and then in a system (using systemfit) with "OLS", "WLS" and "SUR". Quite surprisingly (for myself at least) the results are identical to the last digit. Could someone (please!) give a hint as to what am I

Dear R-help, This is an example in the {Hmisc} manual under rcorr.cens function: > set.seed(1) > x <- round(rnorm(200)) > y <- rnorm(200) > round(rcorr.cens(x, y, outx=F),4) C Index Dxy S.D. n missing uncensored Relevant Pairs Concordant Uncertain 0.4831 -0.0338 0.0462 200.0000

I performed an aov() analysis and got the following results: Df Sum Sq Mean Sq F value Pr(>F) block 1 0.0040 0.0040 0.3282 0.5672 Residuals 269 3.2766 0.0122 Can anyone tell me how to extract the F value column and Pr(>F) column from the summary output of aov analysis? Many thanks in advance, Liqing Eco. Evol. Biol. UCIrvine

Now, we come to more evaluations on http://188.40.87.11:8000/db_default/v4/nts/recent_activity I mainly care about the compile-time and execution time impact for the following cases: pBasic (run 45): clang -O3 -load LLVMPolly.so pNoGenSCEV (run 44): clang -O3 -load LLVMPolly.so -polly-codegen-scev -polly -polly-optimizer=none -polly-code-generator=none pNoGenSCEV_nocan (run 47): same option

Hello at all, working with a dataset I try to optimize a non-linear function with constraint. test<-read.csv2("C:/Users/Herb/Desktop/Opti/NORM.csv") fkt<- function(x){ a<-c(0) s<-c(0) #Minimizing square error for(j in 1:107){ s<-(test[j,2] - (x[1] * test[j,3]) - (x[2] * test[j,4]) - (x[3]*test[j,5]) - (x[4]*test[j,6]) - (x[5]*test[j,7]))^2 a<- a+s} a<-as.double(a)

On 09/08/2013 08:03 PM, Star Tan wrote: > Hello all, > > > I have done some basic experiments about Polly canonicalization passes and I found the SCEV canonicalization has significant impact on both compile-time and execution-time performance. Interesting. > Detailed results for SCEV and default canonicalization can be viewed on: http://188.40.87.11:8000/db_default/v4/nts/32 (or

How can I extract the adjusted R^2 value from an ols object (using rms package)? library(rms) x <- rnorm(10) y <- x + rnorm(10) ols1 <- ols(y ~ x) Typing "ols1" displays adjusted R^2 among other things, but how can I assign it to a variable? I tried str(ols1) but couldn't see where to go from there. Thanks, Mark Seeto