similar to: what's wrong with my "cov"?

Dear all, I need to extract the covariance matrix of my quantile regression estimation to use in a test. My regression is: qf2_1 <- summary(rq(wb2 ~ apv2 + vol2, tau = phi2[1]), cov = TRUE) I can extract the covaraince matrix by using: qf2_1 [3]. However, if I try to use it in the test, it does not work. I only need to transform qf2_1[3] in a matrix 3x3. I have already tried:

Dear all I am trying to use the cov function in the stats library. I have no problem using this function from the console. However, in my R script I received a "function not found" message. Then I called stats::cov(...) and received an error message that the function was not exported. Then I tried stats:::cov (three colons) and received the error Error in get(name, envir =

Hi all, I'm trying to support llvm-cov for a new architecture and I have successfully built compiler-rt for my arch. Following steps shown in https://clang.llvm.org/docs/SourceBasedCodeCoverage.html , I encountered an error for the last step(step of llvm-cov show). The command line was (supposed my arch is XXXX) "llvm-cov show -arch=XXXX ./foo -instr-profile=foo.profdata" and the

Someone can help me? I tried several things and always don't converge # Model library(sem) dados40.cov <- cov(dados40,method="spearman") model.dados40 <- specify.model() F1 -> Item11, lam11, NA F1 -> Item31, lam31, NA F1 -> Item36, lam36, NA F1 -> Item54, lam54, NA F1 -> Item63, lam63, NA F1 -> Item65, lam55, NA F1 -> Item67, lam67, NA F1 ->

Dear All, I am helping our test team migrate from gcov to llvmcov. They currently generate HTML reports using lcov to easily navigate where coverage is missing. However, there does not seem to be a Windows compatible solution for generating HTML reports using the llvm-cov tools. A possible solution to this problem is for llvm-cov to create html pages that include an overall coverage summary

Hi UseRs, I don't want to die beeing idiot... I dont understand the different results between: cor() and cov2cov(cov()). See this little example: > x=matrix(c(0.5,0.2,0.3,0.1,0.4,NA,0.7,0.2,0.6,0.1,0.4,0.9),ncol=3) > cov2cor(cov(x,use="pairwise.complete.obs")) [,1] [,2] [,3] [1,] 1.0000000 0.4653400 -0.1159542 [2,] 0.4653400 1.0000000

Hi all I have a couple of obscure questions for R/Splus experts (which unfortunately isn't me!) I am trying to compute Bayes Factors using some Splus code of Raftery in Gilks et al (1996). Only problem is 1) R doesn't seem to have a robust covariance (cov.mve) which I suspect I need rather than a non-robust classical estimate 2) Splus has cov.mve BUT dgamma in Splus doesn't have a

Hi list, can I extract the cov.unscaled ("the unscaled covariance matrix") from a gls fit (package nlme), like with summary.lm? Background: In a fixed effect meta analysis regression the standard errors of the coefficients can be computed as sqrt(diag(cov.unscaled)) where cov.unscaled is (X'WX). I try do do this with a gls-fit. Thanks, Sven

I recently started using R 2.7.2, and noticed a surprising change in the behavior of var() on NA data: R 2.6.1 (Patched), 2007-11-26, svn.rev 43541, x86_64-unknown-linux-gnu: > stdev(rep(NA,3), na.rm=F) [1] NA > stdev(rep(NA,3), na.rm=T) [1] NA > var(rep(NA,3), na.rm=T, use="complete.obs") [1] NA R 2.7.2 (Patched), 2008-09-02, svn.rev 46491,

Hi All, I want to provide a solution that presents code coverage reports that include the aggregated code-counts across many binaries. Our test engineers currently do this using gcov-mode by merged .gcda data files. We can do a similar merge of the .profraw files, so that the many binaries are represented in one .profdata file; However, llvm-cov will only generate reports based on one binary at

Hi. I have tried to use Package "SEM". As a learning, I try to convert a program running well of EQS which is as follows to SEM: ### EQS ### /SPECIFICATION CAS=100; VAR=5 MAT=COR; ANA=COR; /EQUATIONS V1=*F1+E1; V2=*F1+E2; V3=*F1+*F2+E3; V4=**F1+*F2*E4; V5=*F2+E5; /VAR E1 TO E5=*; F1*1.0; F2=1.0; /COV E1,E2=*; F1,F2=*: /PRINT FIT ALL; /MATRIX ...... /END This is the converted SEM

Xinliang David Li via llvm-dev <llvm-dev at lists.llvm.org> writes: > Harlan Haskins has recently submitted a patch (for review) that implements > --format=html for llvm-cov tool. Please take a look at that patch. For reference, the review thread starts here: http://lists.llvm.org/pipermail/llvm-commits/Week-of-Mon-20160229/336622.html > David > > On Thu, Mar 3, 2016 at

I've been working on adding code coverage support to my ELLCC project (http://ellcc.org) and I thought it would be nice to fun the index page of the HTML output of llvm-cov into something a little prettier and more useful. The initial result is here: http://ellcc.org/coverage/ If there is any interest, I'll submit the llvm-cov changes. -Rich

Hi all, I have written a script in R that simulates genetically informative data - it is posted on my website and available to the public. This is my first time to write a script for use by others and am learning that it isn't as easy as it seems. To the issue. My script runs fine on my machine and on a server I have access to, but a user has written me saying that it crashes the first time

Hello All, I have a covariance matrix, generated by read.table, and cov: co<-cov(read.table("c:/r.x")) X Y Z X 0.0012517684 0.0002765438 0.0007887114 Y 0.0002765438 0.0002570286 0.0002117336 Z 0.0007887114 0.0002117336 0.0009168750 And a weight vector generated by w<- read.table("c:/r.weights") X Y

Hello, Having the matrix d > d value value2 class 1 1 1 x 2 2 2 x 3 3 3 x 4 4 2 x 5 5 1 y 6 11 3 y 7 12 4 z 8 13 5 z 9 14 6 z 10 15 7 z I want to calculate the means and cov matrix for groups x,y,z. I know how to do it the long way. I tried to use tapply and

Hi vedant, The program didn't pass the checking "OF->getArch() != Triple(Arch).getArch()" loadBinaryFormat in CoverageMappingReader.cpp and returned an error. It's because "OF->getArch()" returned null and "Triple(Arch).getArch()" returned XXXX(name of my arch). The returned value of " OF->getArch()" is decided by "

let create a 'zoo' object : library(zoo) date.data = seq(as.Date("01/01/01", format = "%m/%d/%y"), as.Date("06/25/02", format = "%m/%d/%y"), by = 1) len = length(date.data) data1 = zoo(matrix(rnorm(2*len), nrow = len), date.data ) head(data1) Now I want to create an 3 dimensional array (suppose name " var.cov") where,

Hello, Sorry. It may be a stupid question. I have two vectors a<-c(9,3,5) b<-c(3,4,1) How can I get the variance-covariance matrix of these two vectors? I tried cov(a,b), I got a number not a matrix. I tried to transpose vector a and b as t(a) and t(b), it still cannot work. Any suggestions? Thank a lot! -- View this message in context:

If you can help get it working on big-endian systems, we should be able to remove the XFAIL. That seems like the cleanest way out of this. Yuchen sent a patch to llvm-commits on 12/19/13. (I can resend it to you if you don’t have that.) Can you try that out on a BE mips system? On Feb 21, 2014, at 7:11 AM, Reed Kotler <Reed.Kotler at imgtec.com> wrote: > On 02/21/2014 02:58 AM, Daniel