search for: xcoef

Dear R's! I am strugling with cancor procedure in R. I cannot figure out the meaning of xcoef and of yxcoef. Are these: 1. standardized coefficients 2. structural coefficients 3. something else? I have tried to simulate canonical correlation analysis by checking the eigenstructure of the expression: Sigma_xx %*% Sigma_xy %*% Sigma_yy %*% t(Sigma_xy). The resulting eigenvalues were the sa...

...en computed for the svd function, but there might be situations where it was less than this, so I guess the safe option would be to include rank = qr(t(x) %*% y)$rank among the outputs. Then the last four lines of the help might be amended to rk <- cxy$rank all.equal(cor(x %*% cxy$xcoef[, 1:rk, drop=FALSE], y %*% cxy$ycoef[, 1:rk, drop=FALSE]), diag(cxy$cor)) all.equal(cor(x %*% cxy$xcoef[, 1:rk, drop=FALSE]), diag(1, rk)) all.equal(cor(y %*% cxy$ycoef[, 1:rk, drop=FALSE]), diag(1, rk)) which I think is more intuitive. More radically, the xcoef and ycoef compone...

...omial model with one explanatory variable (example Y~X+X^2), with a poisson or binomial error distribution, the predicted values obtained from using the predict() function and those obtained from using the coefficients from the summary table "as is" in an equation of the form Y=INTERCEPT+ XCoef x X + XCoef x X^2, differ considerably. The former are correct and the latter are wrong. This does not occur using lm() or in a glm with family as normal. I conclude that this is due to the link function, predict() having some way of back transforming the data. But if this is so, are the estimated...

...], ArTHarProUpperPCA$x[,2], ArTHarProLowerPCA$x[,2], ArTHarRelTeethPCA$x[,2]) AudioMatrix <- matrix(AudioPCs, nrow=20, ncol=5) VideoMatrix <- matrix(VideoPCs, nrow=20, ncol=5) ArTHarCCA <- cancor(AudioMatrix, VideoMatrix) ArTHarCCA $cor [1] 0.852092 0.833079 0.467436 0.279688 0.026228 $xcoef [,1] [,2] [,3] [,4] [,5] [1,] -0.0118794 0.0305097 -0.058891 -0.0601489 0.029186 [2,] -0.0350698 0.0163593 0.086743 0.0642735 0.100922 [3,] 0.1228351 0.0035069 -0.061669 -0.0019221 0.047723 [4,] -0.0461149 0.0186040 0.057543 -0.0649049 -0.132400 [5,] -0....

...;m trying to use multiple imputation for my MSc thesis. Having good exemples using the Hmisc package, I tried the aregImpute function. But with my own dataset, I have the following error : Erreur dans matxv(X, xcof) : columns in a (51) must be <= length of b (50) De plus : Warning message: In f$xcoef[, 1] * f$xcenter :   la taille d'un objet plus long n'est pas multiple de la taille d'un objet plus court   = longer object length is not a multiple of shorter object length I first tried to "I()" all the continuous variables but the same error occurs with different numbers :...

Dear all, I didn't find any graphical solution in the package "mva" to plot the canonical scores from a CCA (canonical correlation analysis). Does anybody knows how to plot or has anybody already programmed : - the map of the canonical scores, - the graph of the canonical weights, - the correlation circle i.e. the canonical loadings ? Thank you for help ...

...Frank Harrel's aregImpute (in package Hmisc) : > system.time(DataTest.arI<-aregImpute(~ctr+cadredp+persmob+trea+taller +tbox+nbpradio+nbpventil+sitrea,data=DataTest,n.impute=5)) Erreur dans matxv(X, xcof) : columns in a (35) must be <= length of b (33) De plus : Warning message: In f$xcoef[, 1] * f$xcenter : la taille d'un objet plus long n'est pas multiple de la taille d'un objet plus court Timing stopped at: 0.028 0 0.028 > Examples #1 and #2 of the manual gave expected results. Package "mi" (Andrew Gelman and a Columbia team, early development (versi...

...;m trying to use multiple?imputation for my MSc thesis. Having good exemples using the Hmisc package, I tried the aregImpute function. But with my own dataset, I have the following error : Erreur dans matxv(X, xcof) : columns in a (51) must be <= length of b (50) De plus : Warning message: In f$xcoef[, 1] * f$xcenter : ? la taille d'un objet plus long n'est pas multiple de la taille d'un objet plus court ? = longer object length is not a multiple of shorter object length I first tried to "I()" all the continuous variables but the same error occurs with different numbers :...

R-1.7.0 built on NetBSD 1.6, but the validation test suite failed: Machinetype: Intel Pentium III (600 MHz); NetBSD 1.6 (GENERIC) Remote gcc version: gcc (GCC) 3.2.2 Remote g++ version: g++ (GCC) 3.2.2 Configure environment: CC=gcc CXX=g++ LDFLAGS=-Wl,-rpath,/usr/local/lib make[5]: Entering directory `/local/build/R-1.7.0/src/library' >>> Building/Updating