search for: cov2cor

...ger(2) etc) Using integers (instead of "numeric" type) is more efficient as here they're used as indexes and would be converted to integer anyway. Compare > is(1) ... and > is(1L) 1L:p is the sequence 1, 2, 3, ..., p (just like 1:p) Just for curiosity, what is findFn('cov2cor') ? Regards, Kenn* I don't know what findFn('cov2cor') is, I'm a total newbie to R but I created a new, simpler to my opinion function for some descriptive statistics as matrix functions for a matrix called "x": one1=c(rep(1, nrow(x))) means <- t(one1)%*%x/3#row...

...definite!\n") * * }* * * * * * # partial correlation* * Sxx.z <- Sxx - Sxz %*% solve(Szz) %*% t(Sxz)* * print("Sxx.z")* * print(qr(Sxx.z))* * rxx.z <- cov2cor(Sxx.z)[1,2]* * * * return(rxx.z)* *}* *Cov2cor function:-----------------------------------------* *cov2cor<-function (V) * *{* * print("inside cov2cor")* * * * * * p <- (d <- dim(V))[1]* * if (!is.numeric(V) || length(d) != 2L |...

Dear All, I am wondering if there is an R function to convert a covariance matrix to a correlation matrix. I have a covariance matrix sigma and I want to compute the corresponding correlation matrix R from sigma. Thank you very much, Bernard --------------------------------- [[alternative HTML version deleted]]

...is Szz positive definite? zz.ev <- eigen(Szz)$values if(min(zz.ev)[1]<0){ stop("\'Szz\' is not positive definite!\n") } # partial correlation Sxx.z <- Sxx - Sxz %*% solve(Szz) %*% t(Sxz) print(Sxx.z) # this gets printed rxx.z <- cov2cor(Sxx.z)[1,2] #some problem in this function function (V) { print("cov2cor") p <- (d <- dim(V))[1] if (!is.numeric(V) || length(d) != 2L || p != d[2L]) stop("'V' is not a square numeric matrix") Is <- sqrt(1/diag(V))...

...want. However, the following: > k<-6; kk<-(k*(k-1))/2; st.dev<-.5 > x<-matrix(0,5000,kk) > for(i in 1:5000){ > y1<-matrix(rnorm(k^2,mean=0,sd=st.dev),k) > y1<-t(y1)%*%y1 > y1<-y1/k #this keeps the variances similar across different k's > y1<-cov2cor(y1) > x[i,]<- y1[lower.tri(y1)] > } > hist(c(x)) demonstrates that the distribution of corresponding correlations is not uniformly distributed between -1 and 1 (of course there is no reason to suspect that it would be). I have tried using both rcorrmatrix and genPositiveDefMat in th...

Suppose I have a Variance-covariance matrix A. Is there any fast way to calculate correlation matrix from 'A' and vice-versa without emplying any 'for' loop? [[alternative HTML version deleted]]

...t=Chisqtest()) General Linear Hypotheses Multiple Comparisons of Means: Tukey Contrasts Linear Hypotheses: Estimate tx - meta == 0 -22.1626 uv - meta == 0 -0.6932 uv - tx == 0 21.4694 Global Test: Chisq DF Pr(>Chisq) 1 71.94 1 2.217e-17 Warning message: In cov2cor(covm) : diag(.) had 0 or NA entries; non-finite result is doubtful and all pairwise comparisons between treatments are then not possible: summary(pp.coxme.glht,test=adjusted("Westfall")) Error in if (!chkcorr(corr)) stop(sQuote("corr"), " is not a correlation matrix&q...

...reason of the error and in fixing it. Thanks for your attention, Paola Lecca. Here the error: > summary(Fit) Parameters: Estimate Std. Error t value Pr(>|t|) pro1_strength 1 NA NA NA Residual standard error: 2.124 on 10 degrees of freedom Error in cov2cor(x$cov.unscaled) : 'V' is not a square numeric matrix In addition: Warning message: In summary.modFit(Fit) : Cannot estimate covariance; system is singular -------------- next part -------------- An embedded and charset-unspecified text was scrubbed... Name: wild_pp1_mrna.txt URL: <htt...

...method) # is Szz positive definite? zz.ev <- eigen(Szz)$values if(min(zz.ev)[1]<0){ stop("\'Szz\' is not positive definite!\n") } # partial correlation Sxx.z <- Sxx - Sxz %*% solve(Szz) %*% t(Sxz) # this gets printed rxx.z <- cov2cor(Sxx.z)[1,2] # probably error in this function cov2cor return(rxx.z) } for some other datasets this pcor.mat function works fine. The solve.default function is this:--------------- solve.default<-function(a, b, tol = ifelse(LINPACK, 1e-07, .Machine$double.eps),LINPACK = FALSE, ...) {...

Dear all, I used modFit of the package FME to fit a set of ODE to a ste of eperiemntal data. The summary of this fit give me the following error > summary(Fit) Residual standard error: 984.1 on 452 degrees of freedom Error in cov2cor(x$cov.unscaled) : 'V' is not a square numeric matrix In addition: Warning message: In summary.modFit(Fit) : Cannot estimate covariance; system is singular This is due becasue the Hessian matrix has all the entries equal to 0. In these cases, on the help page of modFit, it is suggested to...

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 -0.7278728 [3,] -0.1159542 -0.7278728 1.0000000 > cor(x,use="pairwise.complete.obs") [,1] [,2] [,3] [1,] 1.00...

Hi everyone. Based on a dependent variable (y), I'm trying to generate some independent variables with a specified correlation. For this there's no problems. However, I would like that have all my "regressors" to be orthogonal (i.e. no correlation among them. For example, y = x1 + x2 + x3 where the correlation between y x1 = 0.7, x2 = 0.4 and x3 = 0.8. However, x1, x2 and x3

Dear R-list member, I'm using the function pmnorm() (-->library(mnormt)) within a for-loop. Certain parameter values leads to an error message: "(In sqrt(diag(S)) : NaNs produced, In sqrt(1/diag(V)) : NaNs produced, In cov2cor(S) : diag(.) had 0 or NA entries; non-finite result is doubtful)" obviously because "NaNs" were produced. Is it possible to tell R that it should overleap the iteration which produce the error message? Here is an example code (does not lead to an error message): for (subject in 1...

Greetings, I have a seemingly simple task which I have not been able to solve today and I checked all of the help archives on this and have been unable to find anything useful. I want to construct a symmetric matrix of arbtriray size w/o using loops. The following I thought would do it: p <- 6 Rmat <- diag(p) dat.cor <- rnorm(p*(p-1)/2) Rmat[outer(1:p, 1:p, "<")] <-

...ding required package: lme4 Loading required package: Matrix Loading required package: lattice Attaching package: 'Matrix' The following object(s) are masked from package:stats : xtabs Warning in namespaceImportFrom(self, asNamespace(ns)) : replacing previous import: cov2cor Warning in namespaceImportFrom(self, asNamespace(ns)) : replacing previous import: update Warning in namespaceImportFrom(self, asNamespace(ns)) : replacing previous import: xtabs installing man source files installing indices not zipping data installing help >>> Building/Updat...

...ng vector x, fixing PR#18630, thanks to Ilia Kats. * list.files() on Windows now returns also files with names longer that 260 bytes (the Windows limit is 260 characters). Previously, some file names particularly with 'East Asian' characters were omitted. * cov2cor(<0 x 0>) now works, fixing PR#18423 thanks to Mikael Jagan and Elin Waring. * cov2cor(<negative diagonal>) and similar now give one warning instead of two, with better wording, fixing PR#18424 thanks to Mikael Jagan. * tools:: startDynamicHelp() now ensures p...

...ng vector x, fixing PR#18630, thanks to Ilia Kats. * list.files() on Windows now returns also files with names longer that 260 bytes (the Windows limit is 260 characters). Previously, some file names particularly with 'East Asian' characters were omitted. * cov2cor(<0 x 0>) now works, fixing PR#18423 thanks to Mikael Jagan and Elin Waring. * cov2cor(<negative diagonal>) and similar now give one warning instead of two, with better wording, fixing PR#18424 thanks to Mikael Jagan. * tools:: startDynamicHelp() now ensures p...

...ng vector x, fixing PR#18630, thanks to Ilia Kats. * list.files() on Windows now returns also files with names longer that 260 bytes (the Windows limit is 260 characters). Previously, some file names particularly with 'East Asian' characters were omitted. * cov2cor(<0 x 0>) now works, fixing PR#18423 thanks to Mikael Jagan and Elin Waring. * cov2cor(<negative diagonal>) and similar now give one warning instead of two, with better wording, fixing PR#18424 thanks to Mikael Jagan. * tools:: startDynamicHelp() now ensures p...

...MU3C)) > Cond.lmat <- c(0,1,-1) > Tukey <- glht.mmc(RT2.aov, focus = "Cond", focus.lmat = Cond.lmat) yielding Error in mvt(lower = carg$lower, upper = carg$upper, df = df, corr = carg$corr, : NA/NaN/Inf in foreign function call (arg 6) In addition: Warning message: In cov2cor(covm) : diagonal has non-finite entries > Tukey height Thank you very much for your help! Ullrich Dr Ullrich Ecker Postdoctoral Research Associate Cognitive Science Laboratories School of Psychology (Mailbag M304) Room 211 Sanders Building University of Western Australia 35 Stirli...

hi, I have following data and code; cov <- c (1.670028 ,-1.197685 ,-2.931445,-1.197685,1.765646,3.883839,-2.931445,3.883839,12.050816) cov.matrix <- matrix(cov, 3, 3, dimnames=list(c("y1","x1","x2"), c("y1","x1","x2"))) path.model <- specify.model() x1 -> y1, x1-y1 x2 <-> x1, x2-x1 x2 <->