similar to: covmat argument in princomp() (PR#3682)

Full_Name: Jerome Asselin Version: 1.7.1 OS: Red Hat Linux 7.2 Submission from: (NULL) (24.77.125.119) Setting the parameter na.action=na.omit should remove incomplete records in princomp. However this does not seem to work as expected. See example below. Sincerely, Jerome Asselin data(USArrests) princomp(USArrests, cor = TRUE) #THIS WORKS USArrests[1,3] <- NA princomp(USArrests, cor =

Hello I am creating a linear model with the command net5 = lm( X[,1] ~ PrinComp[,1:5]) where my vector PrinComp looks like this > head(PrinComp[,1:5]) PC1 PC2 PC3 PC4 PC5 [1,] 1.8626055 -3.34190998 -0.5448889 2.8296751 0.3994096 [2,] 3.1124144 -1.68113572 1.7187314 -2.0162583 -0.2935675 [3,] 3.3538049 -0.05471002 -2.9385065 0.6921495 -2.2743761 [4,]

Hi All, I'd like to build a package for the community that replicates the output produced by SAS "proc varclus". According to the SAS documentation, the first few steps are: 1. Find the first two principal components. 2. Perform an orthoblique rotation (quartimax rotation) on eigenvectors. 3. Assign each variable to the rotated component with which it has the higher squared

Dear all I'm unable to find an example of extracting the rotated scores of a principal components analysis. I can do this easily for the un-rotated version. data(mtcars) .PC <- princomp(~am+carb+cyl+disp+drat+gear+hp+mpg, cor=TRUE, data=mtcars) unclass(loadings(.PC)) # component loadings summary(.PC) # proportions of variance mtcars$PC1 <- .PC$scores[,1] # extract un-rotated scores of

In comparing the results of princomp and prcomp I find: 1. The reported standard deviations are similar but about 1% from each other, which seems well above round-off error. 2. princomp returns what I understand are variances and cumulative variances accounted for by each principal component which are all equal. "SS loadings" is always 1. 3. Same happens

Hi everyone, I am trying to get the factor score for each individual case from a principal component analysis, as I understand, both princomp() and prcomp() can not produce this factor score, the principal() in psych package has this option: scores=T, but after running the code, I could not figure out how to show the factor score results. Here is my code, could anyone give me some advice please?

To my knowledge, this has not been reported previously, and doesn't seem to have been changed in R-devel or R-patched. If M is a matrix with coloumn names, and mod <- prcomp(M) # or princomp then predicting a single observation (row) with predict() gives the error Error in scale.default(newdata, object$center, object$scale) : length of 'center' must equal the number of

Hi there! I'm super-happy because I've just finished my semi-auto configurator for Windows machines ^^ I've got a question: must all the users of a VPN share all together their hosts files? i.e. PC1 is linked to PC2 -> PC1 and PC2 must have both /hosts/PC1 and hosts/PC2 PC2 is linked to PC3 -> PC2 and PC3 must have both /hosts/PC2 and /hosts/PC3 Must PC3 have /hosts/PC1

Hi there, I've a training dataset and a test dataset. My aim is to visually allocate the test data within the calibrated space reassembled by the PC's of the training data set, furthermore to keep the training data set coordinates fixed, so they can serve as ruler for measurement for additional test datasets coming up. Please find a minimum working example using the wine dataset below.

--=-hiYzUeWcRJ/+kx41aPIZ Content-Type: text/plain; charset="UTF-8" Content-Transfer-Encoding: 8bit Hi, on March 10 I filed a wishlist bug report asking for the inclusion of some changes to factanal() and the associated print method. The changes were originally proposed by John Fox in 2005; they make print.factanal() display factor correlations if factanal() is called with rotation =

Hi R-community, I am doing a PCA and I need plots for different combinations of axes (e.g., PC1 vs PC3, and PC2 vs PC3) with the arrows indicating the loadings of each variables. What I need is exactly what I get using biplot (pca.object) but for other axes. I have plotted PC2 and 3 using the scores of the cases, but I don't get the arrows proportional to the loadings of each variables on

Dear R-list users, I'm new to principal components and factor analysis. I thought this method can be very useful for me to find relationships between several variables (which I know there is, only don't know which variables exactly and what kind of relation), so as a structure detection method. Now, I'm experimenting with the function prcomp from the mva package. In my source code

Dear Rusers, I have met a difficult problem on explaining the differences of principal component analysis(PCA) between R,S-PLUS and SAS/STATA/SPSS, which wasn't met before. Althought they have got the same eigenvalues, their coeffiecients were different. First, I list my results from R,S-PLUS and SAS/STATA/SPSS, and then show the original dataset, hoping sb. to try and explain it.

pc1(LANa) ----poor connection ----> VPS <--------- PC2(LANb) pc1 and pc2 used to connected directly with tinc, since pc1 used to have WAN IP(pppoe), but the pppoe IP is not WAN IP anymore (ISP changed to let all ADSL user in a LAN). if I let the two pc connect to a VPS with tinc, can later connections between pc1 and pc2 be directly ? for example, ssh from pc1 to pc2 but not proxyed by

Hi ! I've used the example given in the documentation for the prcomp function both in R and SPAD to compare the results obtained. Surprisingly, I do not obtain the same results for the coordinates of the principal composantes with these two softwares. using USArrests data I obtain with R : > summary(prcomp(USArrests)) Importance of components: PC1 PC2

I am doing Principal Component Analysis (PCA) on assets data for household income prediction. The problem is that the assets data are rank ordered (usually binary ... possess car/don't possess car), so the normal correlation is inappropriate for the calculation of the PCA. Instead one has to use the polychoric correlation coefficient. It uses the "random.polychor.pa" package.

Heloo! I have 3 Vpn with 3 servers! pc1 with debian and adr. for ex. 10.10.10.x pc2 with debian and adr. for ex. 10.10.10.y pc3 with debian and adr. for ex. 10.10.10.z On tinc i have pc1 connect to pc2 and pc3 pc2 connect to pc1 and pc3 pc3 connect to pc1 and pc3 Evrithing works fine but i whant to connect from home to this vpn but at my home i have a pppoe (no ip adr., i have user and pass to

Hi there, I'm trying to set up a man-in-the-middle scenario within a VMWare Workstation team, using brctl. What I want is the following: PC1 eth0 >---LAN-segment-1---< eth0 PCMITM eth1 >---LAN-segment-2---< eth0 PC2 Now I did the following on PCMITM (PC man in the middle): ifconfig eth0 down ifconfig eth1 down brctl addbr lnxbr0 brctl addif lnxbr0 eth0 brctl addif lnxbr0 eth1

Hello fellow Rers, I have a no-doubt simple question which is turning into a headache so would be grateful for any help. I want to do a principal components analysis directly on a correlation matrix object rather than inputting the raw data (and specifying cor = TRUE or the like). The reason behind this is I need to use polychoric correlation coefficients calculated with John Fox's

Dear all The following process is about trying to do the " live migration at the same time with 5 Virtual machines ", but there is somthing problem with it. Process: yogi-pc2: # xm migrate --live vm01 pc2 & xm migrate --live vm02 pc2 & xm migrate --live vm03 pc2 & xm migrate --live vm04 pc2 & xm migrate --live vm05 pc2[1] 29983 [2] 29984 [3] 29985 [4]