similar to: how to calculate covariance matrix in R? why cov doesn't work

Thanks in advance! A=c(1, 2,3) B=c (9, 10, 11, 12) I want to get C=c(1*9, 1*10, 1*11, 1*12, ....., 3*9, 3*10, 3*11, 3*12)? C is still a vector with 12 elements Is there a way to do that? -- View this message in context: http://r.789695.n4.nabble.com/how-to-calculate-the-product-of-every-two-elements-in-two-vectors-tp2300299p2300299.html Sent from the R help mailing list archive at Nabble.com.

Hi, I have a set of covariance matrices but not the original data. I want to carry out some exploratory factor analysis. So, I am trying to construct a covariance matrix list as the input for factanal. I can construct a list which includes the cov, the centers, and the n.obs. But it doesn't work. I get an error that says "Error in sqrt(diag(cv)) : Non-numeric argument to mathematical

Hello all! I have a problem with ggplot2 library. I want to do an heat map and the y variables are the year months. If I use the following code, he y values are in alphabetical order, but I want it in month order. The code is: library(reshape) library(ggplot2) library(scales) p <- ggplot(data.m, aes(variable, Month)) + geom_tile(aes(fill = value),

Hello, I am working on seperate the matrix to two matrices but got trouble on doing it. Please give me some suggestions on doing this. Thanks a looooooooooooot! My original matrix m is as follows for example, [,1] [,2] [,3] [1,] 6 8 1 [2,] 5 9 2 [3,] 20 10 3 [4,] 7 11 4 [5,] 8 12 5 [6,] 25 13 6 [7,] 14 14 7 I want to generate two

Hello, I have a vector {a, b1, b2, b3, b4}. How can I calculate the following matrix: var(a) cov(a, b1) cov(a, b2) cov(a, b3) cov(a, b4) cov(a, b1) var(b1) cov(a, b2) cov(a, b3) cov(a, b4) ... ... cov(a, b1) cov(a, b2) cov(a, b3) cov(a, b4) var(b4) I would very appreciate your inputs. Thank you very much. Sincerely, Jialin Huang [[alternative HTML version deleted]]

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

Hello, I am frastruated with this graph, just cannot get what I need. Thank you for any suggestions or help. I really appreciate it. I wrote the following code, but there are 3 problems 1, the red line is added on the graph but without any marker on the y-axis. I want to display the number '.1361' on the y-axis. So people can easily tell 'method 2' gets a constant estimate, which

Anybody knows what functions can be used to calculate variance/covariance with complex numbers? var and cov don't seem to work: > a 1 V1 0.00810014+0.00169366i V2 0.00813054+0.00158251i V3 0.00805489+0.00163295i V4 0.00809141+0.00159533i V5 0.00813976+0.00161850i > var(a) 1 1 1.141556e-09 Warning message: In var(a) : imaginary parts discarded in

Dear R experts, Can R make an usual dotplot just like Minitab and other softwares? I have the following data, and can use dotchart to graph a dotplot: y=c(2.873438152e-01, -8.732895642e-01, 4.579001889e-01, 1.047395204e+00, 8.491182299e-02 , -1.938007105e+00, -1.273708343e+00, 9.848010588e-05, 7.238490734e-01, -1.490552717e+00) dotchart(y, xlab="10 observations from

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, Why cov(y, y) only gives one value, and cov(t(y), t(y)) gives 3x3 NA matrix? Here my y is listed below and it is a 3x1 matrix. I am expecting that if I have a random vector y=[y1 y2 y3]', here " ' " denotes a transposition so that y is a column vector, where y1, y2, y3 are independent random variables... then cov(y, y) should be E[ y * y' ] - E[y] * E[y] ',

Hello, I have a question on export and import data. Thank you for any suggestions. data 'simul' is generated as follows: N <- 20 n <- N/2 nsets <- 10 simul <- matrix(0,nsets,N) th <- c(0,1, 1) for(i in 1:nsets){ simul[i,] <- rnorm(N,mean= rep(th[1:2],N/2),sd=th[3]) } I exported data as follows: write.table(simul,

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

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

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 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

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, after looking around I was not able to get info about these two questions: 1. Is there a function to have a "jackknifed corrected var/cov estimate" (as described in MacKinnon and White 1985) in a standard OLS regression? 2. Does R possess a LAD (Least Absolute Deviation) regression function? Any help? Thanks -- ======================================================== Angelo