search for: comps

Hello all, any help with the following would be appreciated. I am attempting to maximize 28 parameters similtaneously in Optim(). The follwoing is my code: Y<-comp[,9] n<-length(Y) e.1<-.5 e.2<-.5 e.3<-.5 e.4<-.5 e.5<-.5 e.6<-.5 e.7<-.5 e.8<-.5 e.9<-.5 e.10<-.5 e.11<-.5 e.12<-.5 e.13<-.5 e.14<-.5 e.15<-.5 e.16<-.5 e.17<-.5 e.18<-.5

Hi, I've performed an lda and obtained a classification table for some of my data: > efa.dfa<-lda(groups~.,efa.scores.8,CV=T) > str(efa.dfa) List of 5 $ class : Factor w/ 2 levels "1","2": 1 2 1 2 1 1 2 2 1 2 ... $ posterior: num [1:160, 1:2] 0.99083 0.00852 0.93983 0.23186 0.85931 ... ..- attr(*, "dimnames")=List of 2 .. ..$ : chr [1:160]

Dear R helpers, I have been using the loadings function from the multiv library and I get the typical output (see below). When I try to export these results to a file using a write.table() I get the following error message "Error in as.data.frame.default(x[[i]], optional = TRUE) : can't coerce loadings into a data.frame" Any idea why write.table is doing that and any

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

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

Hi!! I'm having trouble selecting 10 out of 41 attributes of the KDD data set. In order to identify the components with the higher variance I'm using princomp. the result i get for summary(pca1) is: Comp.1 Comp.2 Comp.3 Comp.4 Comp.5 Comp.6 Comp.7 Comp.8 Comp.9

I have a question about princomp(mva) that I hope isn't too newbie. I used the sample data from Table 1.1 in "Manly (1986/1994) Multivariate Statistical Methods: a primer. Chapman and Hall" on sparrow body measurements. I rescaled the data to mean 0 and SD 1, and the covariance matrix is: V1 V2 V3 V4 V5 V1 1.0000000 0.7349642 0.6618119

Full_Name: Sahotra Sarkar Version: 2.2.0 OS: Windows XP Professional Submission from: (NULL) (146.6.130.180) The following two commands should give the same results for the eigenvectors but do not (there is a sign reversal for the first one): > summary(princomp(bumpus),loading = TRUE) Importance of components: Comp.1 Comp.2 Comp.3 Comp.4 Comp.5

I have the manual for S+ 6 and I'm trying to use R for the Principle Component Analysis example and I'm getting a few interesting answers... The log is as follows: R : Copyright 2001, The R Development Core Team Version 1.3.0 (2001-06-22) R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type `license()' or

...#39;m having a issue with one object when try to update the attributes in this object previously saved in the database I have one object comp and one object reg they have this relationship comp has_many regs reg belongs_to comp when run use the method valid? like this current_contribuyente.comps.build(params[:comp]).valid? it returns: IndexError (string not matched) And when I try to update directly the comp directly it return this error: @comp = current_contribuyente.comps.find(params[:id]) @comp.update_attributes(params[:comp]) NoMethodError (undefined method `with_indifferent_access...

Hi there, I've just started to work with the great speex encoder on ARM9-based embedded platform. This is my configuration: CPU: Cirrus Logic EP9315 @ 200 MHz (ARM920T) o.s.: Linux 2.6.9-rc2-ep93xx GCC: gcc version 3.3.3 (DENX ELDK 3.1 3.3.3-10) without MaverickCrunch support ogg library: 1.0 speex command line configuration: ./configure --enable-fixed-point --enable-arm4-asm The code is

I am installing R 2.15.1 onto RHEL 6, using gcc 4.7.0 with Intel MKL 10.3.7 and the following environment: export BLAS_LIBS="-Wl,--start-group /usr/caen/intel-12.1/mkl/lib/intel64/libmkl_gf_lp64.a /usr/caen/intel-12.1/mkl/lib/intel64/libmkl_sequential.a /usr/caen/intel-12.1/mkl/lib/intel64/libmkl_core.a -Wl,--end-group -lpthread" export LAPACK_LIBS="-Wl,--start-group

...ary(pls) $ data(NIR) $ testing.plsNOCV <- plsr(y ~ X, 6, data = NIR, method="kernelpls", validation="none") $ NIR.plsCV <- plsr(y ~ X, 6, data = NIR, CV=TRUE, method="kernelpls") $ testing.plsCV <- crossval(testing.plsNOCV) $ R2(NIR.plsCV) (Intercept) 1 comps 2 comps 3 comps 4 comps 5 comps 0.0000 0.9812 0.9825 0.9964 0.9997 0.9999 6 comps 0.9999 $ R2(testing.plsCV) (Intercept) 1 comps 2 comps 3 comps 4 comps 5 comps 0.0000 0.9678 0.9782...

Hi All, Sorry if I ask an obvious thing, I am still new to R ... I created a data frame of given dimensions to which I gave strings as column names. I want to write to elements of the data frame by indexing them with the row number and column name (string). The problem is that I can read elements from the data frame in this way, but I cannot assign to elements in this way. Instead, I get the

Dear All, I've used the X-12-ARIMA or its earlier versions from S+ and R under both Unix and Windows platforms for many years using the klugey approach of calling an executable using in R the system function. I've found this serviceable for the following reasons. 1) Paul Gilbert's hunch is correct that many of the subroutines have extensive IO calls (especially the X-11 engine)

Hello, I tried to do a 'sem' analysis for data of how blueberry consumption by birds is influenced by a pollution gradient, using distance and vegetation structural and composition variables, but I got the following error message: Error in sem.default(ram = ram, S = S, N = N, param.names = pars, var.names = vars, : S must be a square triangular or symmetric matrix This may be very

Dear all, I have a question about the 'sdev' value returned by the princomp function (which does principal components analysis). On the help page for princomp it says 'sdev' is 'the standard deviations of the principal components'. However, when I calculate the principal components for the USArrests data set, I don't find this to be the case: Here is how I

Dear list, I have a question concerning the above mentioned methods in the pls package with respect to the loadings matrix produced by the call. In some work I am doing I have found that the values produced are nearly of the same magnitude but of opposite sign. When I use the example data (sensory) I find this result reproduced. I am prepared to work this through but I have a feeling that

...... 40.85915.... 65.01948.... 55.98204.... 61.71673.... ... ..- attr(*, "dimnames")=List of 2 .. ..$ : chr "X" "X.1" "X.12" "X.13" ... .. ..$ : NULL Because of this I am not able to do a loadings plot >plot(BHPLS1, "loadings", comps = 1:2, legendpos = "topleft", labels = "numbers", >xlab = "nm") Error in loadingplot.default(x, ...) : Could not convert variable names to numbers. What am I doing wrong Thanks in advance [[alternative HTML version deleted]]

Hi I am attempting to do a loadings plot from a plsr object. I have managed to do this using the gasoline data that comes with the pls package. However when I conduct this on my dataset i get the following error message. >plot(BHPLS1, "loadings", comps = 1:2, legendpos = "topleft", labels = "numbers", >xlab = "nm") Error in loadingplot.default(x, ...) : Could not convert variable names to numbers. str(BHPLS1_Loadings) loadings [1:8892, 1:60] -0.00717 0.00414 0.02611 0.00468 -0.00676 ... - attr(*, "d...