similar to: Cases as Variables in Principal Component Analysis?

Hi, I am an old hand at chemistry but a complete beginner at statistics including R computations. My question is whether you can carry out nonlinear multivariate regression analysis in R using neural networks, where the output variable can range from -Inf to + Inf., unlike discriminant analysis where the output is confined to one or zero. The library nnet seems to work only in the latter

Dear List, I am trying to solve a problem by the neural network method(library: nnet). The problem is to express Weight in terms of Age , Sex and Height for twenty people. The data frame consists of 20 observations with four variables: Sex, Age, Height and Weight. Sex is treated as a factor, Age and Weight are variables normalized to unity, as usual. I wanted to construct a neural network, and so

Hi R users! One thing I cannot understand with R is the frequently appearing " Correlation of coefficients". I do not find a through going explanation of this concept either on the help pages of R or on the internet. A Google search has shown many examples of R/S-Plus outputs but no explanations of meaning. I am afraid this turns out to be a silly and unworthy question. Would anyone be

On 5/13/2008 10:27 AM, Yukihiro Ishii wrote: > Hi Rusers! > > I am ashed of asking such a simple question. > > X<-matrix(rnorm(24), 4) > X0<-apply(X,2,mean) > > What I want is a matrix which consists of colums such as X[,1]--X0[1]. > > X-X0 doesn't work. > > Perhaps apply function? scale(X, scale=FALSE) ?scale > Thanks in advance. > >

Matz claims 1.8.3 might be released in April. If we''re lucky, maybe it will have the Windows socket connection fix applied. (Although the patch has been hanging around since last June... but maybe they just needed some prodding. :) ) Then RubyTorrent will be much more usable on Windows. ----- Forwarded message from Yukihiro Matsumoto <matz@ruby-lang.org> ----- Date: Tue, 8 Feb

Hi R-users, I would like to find the goodness of fit using Chi-suare test for my data below: xobs=observed data, xtwe=predicted data using tweedie, xgam=predicted data using gamma > xobs <- c(223,46,12,5,7,17) > xtwe <- c(217.33,39,14,18.33,6.67,14.67) > xgam <- c(224.67,37.33,12.33,15.33,5.33,15) > chisq.test(xobs, xtwe = xtwe, rescale.p = TRUE) Error in chisq.test(xobs,

Hi !! <p> I am just now reading Vorbis I specifications . I ahve some quries in that regading overlap add and sqaure polar mapping . I am writting this mail with the hope that ,some one will resolve my quries. <p> 1. After IMDCT , to remove the aliasing , we do overlap and add . For that the window should have following properties -------------> hk =

Hello. This is a follow by myself. I added the following lines (with + marking) to /etc/network/interfaces and problem is solved. On 2007/01/31, at 20:14, Toshinao Ishii wrote: > > auto lo > iface lo inet loopback > + auto eth0 + iface eth0 inet manual > # The primary network interface > auto xenbr0 > iface xenbr0 inet static > address 10.140.2.84 >

Ruby event on November 3, 2011 at MacKenzie Room, Stanford University. Program will include, 1) keynote speeches by Yukihiro “Matz” Matsumoto and Derek Collison, CTO, VMware Inc. and 2)Silicon Valley Ruby Innovator Award Competition, a preliminary competition for the 2012 Fukuoka Ruby Award. Please check the details from the following link and register for the event.

We in the JRuby project are working to get Rails to work successfully. However, the array-indexed block parameter is not something currently supported in JRuby: x = {} [1,2].each {|x[:foo]|} This is not used extensively in the Rails code, but it''s used enough to cause things to break in JRuby. We have been modifying the above to use a temporary local variable, but obviously

Hi all, I am wondering in R, suppose I did the principal component analysis on training data set and obtain the rotation matrix, via: > pca=prcomp(training_data, center=TRUE, scale=FALSE, retx=TRUE); Then I want to rotate the test data set using the > d1=scale(test_data, center=TRUE, scale=FALSE) %*% pca$rotation; > d2=predict(pca, test_data, center=TRUE, scale=FALSE); these two

Dear R users the factanal pacakge is always MLE, which package can do varimax rotation with the results from princomp ? thank you yong

I have data set with binary responses. I would like to conduct polychoric principal component analysis (pPCA). I know there are several packages used in PCA but I could not find one that directly estimate pPCA and graph the individuals and variables maps. I will appreciate any help that expand these reproducible scripts. #How to conduct polychoric principal component analysis pPCA using #either

Hi: How i can make principal component plots with R. thanks Jorge -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To: r-help-request at stat.math.ethz.ch

Hi everyone, I did a principal component analysis (princomp) on a dataset I have, I plotted the first two columns and labeled the points by their index number. I observed that most index sequences (points 50:65 for example) kind of form arc shape trajectories on the graph (even loops), some of those seem to converge at some particular location and those specific patterns just happen to have some

Is there any R function to perform factor analysis using Principal Component Method? why factanal() method is " always "mle" " ?

Hi, I am trying to run PCA on a set of data with dimension 115*300,000. The columns represnt the snps and the row represent the individuals. so this is what i did. #load the data code<-read.table("code.txt", sep='\t', header=F, nrows=300000) # do PCA # pr<-prcomp(code, retx=T, center=T) I am getting the following error message "Error: cannot allocate vector of

Dear Forum, I have a class variable 1 (populations A-E), and two other class variables, variable 2 and variable 3. What I want is to see if the combination of var 2 and var 3, will give me a pattern that allows to distinguish populations. I found several packages like ade4, with pcaiv function and factoMineR. but there are not working. Using the ade4 package, when I try to build the pca: pca1

Hi, I am trying to do a Principal component analysis on histogram data. Basically, I have a group of subjects and for each of them, I have a column of bin-counts (vis-a-vis intervals) and a corresponding column of frequencies (or normalized frequencies). The bin counts are the same for all the subjects. I also have a group-averaged histogram (with the same bin counts and a column of frequencies)

Hi , To my knowledge, there're two functions that can do principal component analysis, princomp and prcomp. I don't really know the difference; the only thing I know is that when the sample size < number of variable, only prcomp will work. Could someone tell me the difference or where I can find easy-to-read reference? To access the first PC using princomp: