similar to: PCA and gglot2

Hi there, I've a training dataset and a test dataset. My aim is to visually allocate the test data within the calibrated space reassembled by the PC's of the training data set, furthermore to keep the training data set coordinates fixed, so they can serve as ruler for measurement for additional test datasets coming up. Please find a minimum working example using the wine dataset below.

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

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 All, I have tried to find an answer within documentation, but I cannot: o How can call a class "slot" without knowing the name a priori? E.g., let's say I use the "pcaMethods" library to create a "pcaRes" object. How can I call parts of that object without using the specific names of the object in the call? example code: library(pcaMethods)

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]]

[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

Is there an option to draw concentration ellipses in biplots ? It seems really nice to summarize large number of points of each group. Cheers../ Murli

hello all R experts, how do I calculate the reliability between the two groups using the ICCs? I'll appreciate your reply, Thanks Sincerely, Supreet kaur, Biomedical research engineer, Nationwide Childrens Hospital, Columbus, OH (614)355-3509 [[alternative HTML version deleted]]

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

Hi, I need to export to LaTex the summary of a PCA. So: myPCA <- prcomp(myDF) mySummary <- summary(myPCA) # print(xtable(mySummary)) How can I export to LaTeX not all the summary but only the first nPCs?? Best Riccardo

Hola compañeros de la lista, qué tal. Estoy haciendo un análisis de componentes principales utilizando las funciones "dudi.pca" (paquete "ade4") y "PCA" (paquete "FactoMineR"). Sucede que al comparar las coordenadas de cada individuo que obtiene cada función, las que corresponden al segundo componente principal tienen idéntica magnitud pero con

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'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

Hi, Is there a package to perform a sine function fitting to XY data? Thx, Ashz -- View this message in context: http://r.789695.n4.nabble.com/Sine-function-fitting-tp3000156p3000156.html Sent from the R help mailing list archive at Nabble.com.

Instalo ade4 correctamente y no me abren los datos como por ejemplo data(bsetal97) ¿Qué piensan de eso? De: r-help-es-bounces en r-project.org [mailto:r-help-es-bounces en r-project.org] En nombre de Francesc Carmona Enviado el: Tuesday, October 01, 2013 7:30 AM Para: r-help-es en r-project.org Asunto: Re: [R-es] Análisis de componentes principales con ade4 y FactoMineR Por definición

Hi, I am interested in ggplot2 and I found this lattice code very interesting (http://addictedtor.free.fr/graphiques/graphcode.php?graph=48). Code: library(lattice) lattice.options(default.theme = canonical.theme(color = FALSE)) tmp <- expand.grid(geology = c("Sand","Clay","Silt","Rock"), species = c("ArisDiff",

Hi, I have 20*60 data matrix (with some NAs) and I wish to perfom a Pearson correlation coefficient matrix as well as simple linear regression equation and coefficient of determination (R2) for every possible combination. Any tip/idea/library/script how do to so. Thanks, As hz -- View this message in context:

Hi, I have this script: dat <- data.frame(X = halistat$Date,Y1 = halistat$avg,Y2 = halistat$stdev) ggplot(data = dat, aes(x = X, y = Y1, ymin = Y1 - Y2, ymax = Y1 + Y2)) + geom_point() + # points at the means geom_line() + # if you want lines between pints geom_errorbar() # error bars, Y1 - Y2 and Y1 + Y2 halistat$Date values: 29/1/10 21/2/10 30/3/10 30/4/10 30/5/10 In the resulted

Dear all, I generated a Correlograms and used the panel.ellipse (confidence ellipse and smoothed line) option. Is there a way to get instead of the smoothed line the linear regression? Thanks, As hz -- View this message in context: http://r.789695.n4.nabble.com/Correlograms-and-linear-regression-tp2331071p2331071.html Sent from the R help mailing list archive at Nabble.com.

Hi, Based on some modification that I did to the R Cookbook Graphs Scatterplots code, link:http://wiki.stdout.org/rcookbook/Graphs/Scatterplots%20(ggplot2) I have some questions and I will appreciate a help: - How do I change the legend title? - How can I change the for each linear regression its color and linetype? - How can I add for both the linear regression lines their equations and Rseq