similar to: Oriented PCA in R?

Ooops...I meant "formulations shouldn't be difficult" -------- Original Message -------- Subject: Re: [R] Kernel Fisher Discriminant in R? Date: Wed, 01 Dec 2004 08:05:38 +0200 From: Gorden Jemwa <jemwa at sun.ac.za> To: huh at rti.org CC: r-help at stat.math.ethz.ch You could us the kernlab package as a building block. Implementation of Kernel Fisher Discriminant Analysis

Dear R Admins, I received an unsolicited e-mail from BlueInference as an R user. Does it mean that R that our e-mails (and names) is sharing it's user database with third parties without our consent? Or perhaps the BlueInference guys are using an e-mail address miner to get our contact details? [SNIP] Dear Gorden Jemwa, As a fellow R user, I am sure you agree with me that R is a

Hello can anyone help, I have been running the following script to obtain a PCA plot but the end result is rather disappointing as the points are very very small and there are no titles etc geochemdata<-read.csv(file.choose(),header=TRUE) names(geochemdata) library(vegan) bstick<-function(n, tot.var=1) rev(cumsum(tot.var/n:1)/n) geopca<-rda(geochemdata, scale=TRUE) geopca

Good day all. This is to thank all those who have helped in fixing this problem. Starting with a text book was indeed a problem, however, that gave me a clue of what I was looking for. This, with your contributions added to other materials I got on the net, put me on the right track. Thank you so much. Warmest regards Ogbos On 31 January 2010 14:07, S Ellison <S.Ellison@lgc.co.uk> wrote:

Hi all, I am attempting to run PCA on a matrix (nrow=66, ncol=84) using 'prcomp' (stats package). My data (referred to as 'Q' in the code below) are separate river streamflow gaging stations (columns) and peak instantaneous discharge (rows). I am attempting to use PCA to identify regions of that vary together. I am entering the following command:

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

Dear all, I am looking for some interactive study materials on Principal component analysis. Basically I would like to know what we are actually doing with PCA? What is happening within the dataset at the time of doing PCA. Probably a 3-dimensional interactive explanation would be best for me. I have gone through some online materials specially Wikipedia etc, however what I need a "movable

Hello, I'm attempting to run a PCA on an example data set. I ran it just fine, but I don't know how to few the output? I listed what the variable got stored in it, but I don't know how I can get anything else out of it. Are there other ways to view the results? Also, I'm confused about the last line "6 variables and 8 observations" Aren't the rows the

A bit of a newbee to R and factor rotation I am trying to understand factor rotations and their implementation in R, particularly the GPArotation library. I have tried to reproduce some of the examples that I have found, e.g., I have taken the values from Jacksons example in "Oblimin Rotation", Encyclopedia of Biostatistics

Could any body help to how to do analysis of PCA with raw data in R software. I will send you the data then. Regards Abdul Hanan

Hi, I am learning how to do principal component analysis in R. However, since I am family with only a few built-in functions like prcomp, sd, cor, I started manually with examples in text books while trying to use the few functions I know to manipulate what they have in the text. From the example in the text I obtained a data set. Using cor and cov, I calculated the correlation and covariance of

Hi, I was wondering if anybody might have a reference for me: My R code is growing and getting more and more confusing. Thus, I figure it's time to switch to object-oriented again. I have done oo programming in C++ and Java before but the first few tutorial on R oo were a bit confusing for me. Is there any brief tutorial on oo programming in R especially for people who have done oo in Java

[Moderator's Note: This message needed manual interaction by me, since the attachment originally was declared as ``application/octet-stream'' even though it was only plain text. We do not allow octet-stream (aka binary!) attachments on our mailing list -- for virus/spam filtering reasons. -- MM] We have also encountered the problem Douglas

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.

Hi All, I have been trying to get to plot my PCA legend outside of the PCA plot, but success still alludes me. Can you guys please advise how I can achieve this. I used locater() to obtain coordinates for below the Comp.1 axis. Using these coordinates the legend disappears. Below is the code for the PCA and legend. Thanks in advance for the help. Regards Tinus r.cols <-

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

Hola, He mirado por encima el conjunto y el posible error. Como alternativa, mira la solución que se propone aquí: http://stats.stackexchange.com/questions/24450/how-to-highlight-predefined-groups-in-pca-individual-map Y como sugerencias: - Limpiaría un poco el conjunto para quitar las filas que tienen todas sus columnas con NA. ¿Qué sentido tiene dejarlas? - Y haría el ejercicio de

Hola, Ya está disponible igualmente la presentación de Pedro Concejero sobre el "PCA con matrices sparse para clasificación automática de contenidos (p.ej. películas).<http://concejero.wdfiles.com/local--files/home/PCA_movies_matrices_sparse.ppt> " Está en la página del grupo dentro de la de la Asociación (reunión del 31-octubre) http://r-es.org/tiki-index.php?page_ref_id=43 El

Hi There, I'm attempting to plot 10 values on a three-dimensional PCA with text labels next to each point. While i have no trouble doing this on 2D plots using the 'text' or 'textxy' function, I cannot find a function to do this on a 3D plot. I am using princomp for my PCA: >PCA<-princomp(eucdata, cor=TRUE) >PCA$scores [,1:3] # the three principal components i

Hello, I am trying to complete a PCA on a set of standardized ring widths from 8 different sites (T10, T9, T8, T7, T6, T5, T3, and T2). The following is a small portion of my data: T10 T9 T8 T7 T6 T5 T3 T2 1.33738 0.92669 0.91146 0.98922 0.9308 0.88201 0.92287 0.91775 0.82181 1.05319 0.92908 0.97971 0.95165 0.98029 1.14048 0.77803 0.88294 0.96413 0.90893 0.87957 0.9961 0.74926 0.71394 0.70877