similar to: tc and multiple ip on a device

Hello, not understanding the output of prcomp, I reduce the number of components and the output continues to show cumulative 100% of the variance explained, which can't be the case dropping from 8 components to 3. How do i get the output in terms of the cumulative % of the total variance, so when i go from total solution of 8 (8 variables in the data set), to a reduced number of

Hey, I need some help. I want to obtain a cross validation for a regression model (binary response) but I got an error with CVbinary. Well I did this: fit <- lm(resp ~ PC1 + PC2 + PC3 + PC4 + PC5 + PC6 + PC7 + PC8 + PC9+PC10+PC11+PC12+PC13+PC14+PC15+PC16+PC17+PC18+PC19+PC20+PC21+PC22+PC23+PC24+PC25+PC26+PC27+PC28, data = dexp.cp, family=binomial()) CVbinary(fit) Error in sample(nfolds, m,

Hi, I saved as a matrix a summary of a PCA analysis and I've used barplot to plot the PCA variances. I would like to print on the same graphic the values of my matrix m1 - in other words the summary of my PCA analysis. I can do it very painstaking with text for each row and make sure that everything aligns and so on but i wonder if there is a better method than that. My summary follows:

Following from the R-help thread of March 22 on "Memory usage in prcomp", I've started looking into adding an optional 'rank.' argument to prcomp allowing to more efficiently get only a few PCs instead of the full p PCs, say when p = 1000 and you know you only want 5 PCs. (https://stat.ethz.ch/pipermail/r-help/2016-March/437228.html As it was mentioned, we already

x86 pm : provide CC7/PC2 residency Sandy bridge introduces new MSR to get cc7/pc2 residency (core C-state 7/package C-state 2). Print the cc7/pc2 residency when on sandy bridge platform. Signed-off-by: Yang Zhang <yang.z.zhang@intel.com> diff -r 662dbf6ee71c tools/libxc/xc_pm.c --- a/tools/libxc/xc_pm.c Mon Oct 24 18:01:07 2011 +0100 +++ b/tools/libxc/xc_pm.c Fri Oct 28

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.

Greets to the list! I am aware that this topic has been discussed several times. And I've read quite some related posts [1]. Yet, can't seem to give a solution to my problem. I have 6 data frames consisting of 6 rows x 7 columns put together from other data.frames. Something like: a b c d e f g v1 # # # # # # # v2 # # # # # # # v3 # # # # # # # v4 # # # # # # # v5 # # # # # # # v6

I agree with Kasper, this is a 'big' issue. Does your method of taking only n PCs reduce the load on memory? The new addition to the summary looks like a good idea, but Proportion of Variance as you describe it may be confusing to new users. Am I correct in saying Proportion of variance describes the amount of variance with respect to the number of components the user chooses to show? So

I am getting the following erro rmessage in ordistep. I have a number of similarly structured datasets using ordistep in a loop, and the message only occurs for some of the datasets. I cannot include a reproducible sample - the specific datasets where this is occur ing are fairly large and there are several pcnm's in the rhs of the formula. thanks for any pointers that may allow me to

> On 25 Mar 2016, at 10:41 am, peter dalgaard <pdalgd at gmail.com> wrote: > > As I see it, the display showing the first p << n PCs adding up to 100% of the variance is plainly wrong. > > I suspect it comes about via a mental short-circuit: If we try to control p using a tolerance, then that amounts to saying that the remaining PCs are effectively zero-variance, but

Hi guys, I am new to R, so sorry if my problem seems trivial. Sometimes I encounter some lists, which I cannot index their components with [ . ] For instance the prcomp() function returns a 'prcomp' object whose components are some 'lists'. the second component is a list that comtains the following: > mylist <- churn[2] > class(mylist) [1] "list" >

- use consistent error values (stop mixing of [positive] errno values with literal -E... ones) - properly format output - don''t use leading zeros in decimal output - move printing of average frequency into P-state conditional (rather than a C-state one) - don''t print some C-state related info when CPU idle management is disabled in the hypervisor - use calloc() for array

Hi all, I think I may be confused by different people/programs using the word rotation differently. Does prcomp not perform rotations by default? If I understand it correctly retx=TRUE returns ordinated data, that I can plot for individual samples (prcomp()$x: which is the scaled and centered (rotated?) data multiplied by loadings). What does it mean that the data is rotated from the

Martin, I fully agree. This becomes an issue when you have big matrices. (Note that there are awesome methods for actually only computing a small number of PCs (unlike your code which uses svn which gets all of them); these are available in various CRAN packages). Best, Kasper On Thu, Mar 24, 2016 at 1:09 PM, Martin Maechler <maechler at stat.math.ethz.ch > wrote: > Following from

Hi I have a script which is designed to gather data from individual columns from a file, which is an output from an instrument. the file has multiple sections and each a section has data under each column (vars), I am using the name of the column as a variable to gather the column ID using vidx<-grep(vars[vi],gsub("[[:punct:]]","",strrl1[[datbeg-1]]),ignore.case=T) the

I am getting the following erro rmessage in ordistep. I have a number of similarly structured datasets using ordistep in a loop, and the message only occurs for some of the datasets. I cannot include a reproducible sample - the specific datasets where this is occur ing are fairly large and there are several pcnm's in the rhs of the formula. thanks for any pointers that may allow me to

As I see it, the display showing the first p << n PCs adding up to 100% of the variance is plainly wrong. I suspect it comes about via a mental short-circuit: If we try to control p using a tolerance, then that amounts to saying that the remaining PCs are effectively zero-variance, but that is (usually) not the intention at all. The common case is that the remainder terms have a roughly

Dear R user, I want to do sparse principal component analysis (spca). I am using elastic net package for this and spca() and the code is following from the example. My question is How can I decide the *K =? *and *para=c(7,4,4,1,1,1)) . So, here k=6 i.e the no of Principal Components. and each pcs say , * ** pc1 number of non zero loading is 7 pc2 number of non zero loading

> On 25 Mar 2016, at 10:08 , Jari Oksanen <jari.oksanen at oulu.fi> wrote: > >> >> On 25 Mar 2016, at 10:41 am, peter dalgaard <pdalgd at gmail.com> wrote: >> >> As I see it, the display showing the first p << n PCs adding up to 100% of the variance is plainly wrong. >> >> I suspect it comes about via a mental short-circuit: If we

Hi All: I am running prcomp on a very large array, roughly [500000, 3650]. The array itself is 16GB. I am running on a Unix machine and am running ?top? at the same time and am quite surprised to see that the application memory usage is 76GB. I have the ?tol? set very high (.8) so that it should only pull out a few components. I am surprised at this memory usage because prcomp uses the SVD