I don't think cov.wt uses frequency weights. However, I don't think this is mentioned in its help page.
Here is some information about the difference: http://stats.stackexchange.com/questions/61225/correct-equation-for-weighted-unbiased-sample-covariance The frequency version isn't hard to program (below), and is probably somewhere in R already. Chris mywtcov <- function(x, frqwt=rep(1,nrow(x)), unbiased=TRUE) { if (is.data.frame(x)) x <- as.matrix(x) n <- sum(frqwt) center <- colSums(frqwt * x) / n xcw <- sqrt(frqwt) * sweep(x, 2, center, check.margin = TRUE) cov <- crossprod(xcw) cov <- if (unbiased) { cov/(n - 1) } else { cov/n } list(cov=cov, center=center, unbiased=unbiased) } mywtcov(mydata) mywtcov(mytable[,1:2,], mytable[,3]) all.equal(mywtcov(mytable[,1:2,], mytable[,3])$cov, xcov) -----Original Message----- From: Emilio Torres Manzanera [mailto:tor...@uniovi.es] Sent: Sunday, March 30, 2014 6:31 PM To: r-help@r-project.org Subject: [R] cov.wt gives different results from other (co)variance functions (cov, wtd.var) Dear Sir, I am not sure about the precision of the cov.wt function. It seems that it provides different results when using frequency weights. This discrepancy only occurs with the covariance matrix, not with the correlation matrix. Do you know to how to solve this issue? Thank you Best regards, Emilio rm(list=ls()) library(plyr) library(Hmisc) mydata <- iris[,1:2] xcor <- cor(mydata) xcov <- cov(mydata) all.equal(cov.wt(mydata)$cov,xcov) # OK ## Now, we use frequency weights mytable <- count(mydata) # Compute frequency table all.equal(wtd.var(mytable[,1],weights=mytable$freq), xcov[1,1]) # OK (Hmisc::wtd.var and cov) # But with cov.wt result <- cov.wt(mytable[,1:2],wt=mytable$freq,cor=TRUE) all.equal(result$cov, xcov) # Wrong! # "Mean relative difference: 0.003579418" all.equal(wtd.var(mytable[,1],weights=mytable$freq), result$cov[1,1]) # Wrong! # "Mean relative difference: 0.003592277" all.equal(result$cov[1,1], xcov[1,1]) # Wrong! # "Mean relative difference: 0.003579418" # The correlations are equal all.equal(result$cor, xcor) # OK sessionInfo() R version 3.0.3 (2014-03-06) Platform: i686-pc-linux-gnu (32-bit) locale: [1] LC_CTYPE=es_ES.UTF-8 LC_NUMERIC=C [3] LC_TIME=es_ES.UTF-8 LC_COLLATE=es_ES.UTF-8 [5] LC_MONETARY=es_ES.UTF-8 LC_MESSAGES=es_ES.UTF-8 [7] LC_PAPER=es_ES.UTF-8 LC_NAME=C [9] LC_ADDRESS=C LC_TELEPHONE=C [11] LC_MEASUREMENT=es_ES.UTF-8 LC_IDENTIFICATION=C attached base packages: [1] splines grid stats graphics grDevices utils datasets [8] methods base other attached packages: [1] Hmisc_3.14-0 Formula_1.1-1 survival_2.37-7 lattice_0.20-27 [5] plyr_1.8 loaded via a namespace (and not attached): [1] cluster_1.15.1 latticeExtra_0.6-26 RColorBrewer_1.0-5 -- ================================================= Emilio Torres Manzanera Fac. de Comercio - Universidad de Oviedo c/ Luis Moya 261, E-33203 Gijón (Spain) Tel. 985 182 197 email: tor...@uniovi.es ********************************************************** Electronic Mail is not secure, may not be read every day, and should not be used for urgent or sensitive issues ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
