Displaying 20 results from an estimated 7000 matches similar to: "princomp scores reproduced"
2010 Nov 30
3
pca analysis: extract rotated scores?
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
2004 Sep 14
3
Signs of loadings from princomp on Windows
I start a clean session of R 1.9.1 on Windows and I run the following code:
> library(MASS)
> data(painters)
> pca.painters <- princomp(painters[ ,1:4])
> loadings(pca.painters)
Loadings:
Comp.1 Comp.2 Comp.3 Comp.4
Composition 0.484 -0.376 0.784 -0.101
Drawing 0.424 0.187 -0.280 -0.841
Colour -0.381 -0.845 -0.211 -0.310
Expression 0.664 -0.330 -0.513
2010 Jan 21
1
why scores are different in rda() and princomp()
hello,
I am doing PCA in R using some habitat factors, and I used the function result1=rda() and result2=princomp(),then pick up scores of the result1 and result2 using scores(),but the scores are significantly different,i do not know the meaning of it.
Best wishes!
Cheng
2004 Nov 03
2
Princomp(), prcomp() and loadings()
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
2005 May 23
1
Can't reproduce clusplot princomp results.
Dear R folk:
Perhaps I'm just dense today, but I am having trouble reproducing the
principal components plotted and summarized by clusplot. Here is a brief
example using the pluton dataset. clusplot reports that the first two
principal components explain 99.7% of the variability. But this is not what
princomp is reporting. I would greatly appreciate any advice.
With best regards,
-- Tom
2011 Jan 28
3
how to get coefficient and scores of Principal component analysis in R?
Dear All,
It might be a simple question. But I could not find the answer from function “prcomp” or “princomp”. Does anyone know what are the codes to get coefficient and scores of Principal component analysis in R?
Your reply will be appreciated!
Best
Zunqiu
[[alternative HTML version deleted]]
2010 Apr 16
1
PCA scores
Hi all,
I have a difficulty to calculate the PCA scores. The PCA scores I calculated
doesn't match with the scores generated by R,
mypca<-princomp(mymatrix, cor=T)
myscore<-as.matrix(mymatrix)%*%as.matrix(mypca$loadings)
Does anybody know how the mypca$scores were calculated? Is my formula not
correct?
Thanks a lot!
Phoebe
[[alternative HTML version deleted]]
2003 Jan 30
3
Principal comp. scores in R
Hello, I am trying to run a PCA in R and I cannot get the PC scores for
each of the values. Using pcX <- princomp(X) then loadings(pcX) I can get a
listing of the eigenvectors but not the actual PC scores for each value in
the dataset. I greatly appreciate any help anyone can offer
Thanks
Ken
2005 Mar 24
1
RE: [R] Mapping actual to expected columns for princomp object
[Re-directing to R-devel, as I think this needs changes to the code.]
Can I suggest a modification to stats:predict.princomp so that it will check
for column (variable) names?
In src/library/stats/R/princomp-add.R, insert the following after line 4:
if (!is.null(cn <- names(object$center))) newdata <- newdata[, cn]
Now Dana's example looks like:
> predict(pca1, frz)
Error in
2006 Jul 31
1
How does biplot.princomp scale its axes?
I'm attempting to modify how biplot draws its red vectors (among other
things). This is how I've started:
Biplot <- function(xx, comps = c(1, 2), cex = c(.6, .4))
{
## Purpose: Makes a biplot with princomp() object to not show arrows
## ----------------------------------------------------------------------
## Arguments: xx is an object made using princomp()
##
2003 May 06
2
R vs SPSS output for princomp
Hi,
I am using R to do a principal components analysis for a class
which is generally using SPSS - so some of my question relates to
SPSS output (and this might not be the right place). I have
scoured the mailing list and the web but can't get a feel for this.
It is annoying because they will be marking to the SPSS output.
Basically I'm getting different values for the component
2003 Aug 08
1
covmat argument in princomp() (PR#3682)
R version: 1.7.1
OS: Red Hat Linux 7.2
When "covmat" is supplied in princomp(), the output value "center" is all
NA's, even though the input matrix was indeed centered. I haven't read
anything about this in the help file for princomp(). See code below for an
example: pc2$center is all NA's.
Jerome Asselin
x <- rnorm(6)
y <- rnorm(6)
X <- cbind(x,y)
2007 May 10
1
A simple question about PRINCOMP
Hi,
I just wonder if this is a rounding error by the princomp command in R.
Although this does not make much sense, using a hypothetical dataset, a,
a<-matrix(runif(1000),100,10)
I did PCA with the princomp, and compared it with the results estimated
with the eigen and the prcomp commands. And I found some differences in
the results: opposite signs in the loadings; slight differences in
2010 Jan 18
2
Rotating pca scores
Dear Folks
I need to rotate PCA loadings and scores using R.
I have run a pca using princomp and I have rotated PCA results with
varimax. Using varimax R gives me back just rotated PC loadings without
rotated PC scores.
Does anybody know how I can obtain/calculate rotated PC scores with R?
Your kindly help is appreciated in advance
Francesca
[[alternative HTML version deleted]]
2012 Apr 25
1
pca biplot.princomp has a bug?
x=rmvnorm(2000, rep(0, 6), diag(c(5, rep(1,5))))
x=scale(x, center=T, scale=F)
pc <- princomp(x)
biplot(pc)
There are a bunch of red arrows plotted, what do they mean? I knew that the
first arrow labelled with "Var1" should be pointing the most varying
direction of the data-set (if we think them as 2000 data points, each being
a vector of size 6). I also read from
2007 Feb 13
1
Questions about results from PCAproj for robust principal component analysis
Hi.
I have been looking at the PCAproj function in package pcaPP (R 2.4.1) for
robust principal components, and I'm trying to interpret the results. I
started with a data matrix of dimensions RxC (R is the number of rows /
observations, C the number of columns / variables). PCAproj returns a list
of class princomp, similar to the output of the function princomp. In a
case where I can
2009 Jan 14
1
Adressing list-elements
Dear all,
I'm using R 2.8.1 under Vista.
I programmed a Simulation with the code enclosed at the end of the eMail.
After the simulation I want to analyse the columns of the single
simulation-runs, i.e. e.g. Simulation[[1]][,1] sth. like that but I
cannot address these columns...
Can anybody please help?
Best,
Thomas
############################ CODE ############################
2009 Oct 19
2
What is the difference between prcomp and princomp?
Some webpage has described prcomp and princomp, but I am still not
quite sure what the major difference between them is. Can they be used
interchangeably?
In help, it says
'princomp' only handles so-called R-mode PCA, that is feature
extraction of variables. If a data matrix is supplied (possibly
via a formula) it is required that there are at least as many
units as
2012 Oct 19
1
factor score from PCA
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?
2005 Sep 16
1
About princomp
Hi,
I run the example for princomp for R211
I got the following error for biplot
> ## The variances of the variables in the
> ## USArrests data vary by orders of magnitude, so scaling is appropriate
> (pc.cr <http://pc.cr> <- princomp(USArrests)) # inappropriate
Erreur dans cov.wt(z) : 'x' must contain finite values only
> princomp(USArrests, cor = TRUE) # =^=