search for: pca

...1971) and I found the function 'biplot', inside of the package 'stats', useful but, a bit limited. So, I'm thinking to start a colaborative package to enhance this methods to other multivariate methods. In this way, I would like to start it, making public a new function (biplot.pca, still in development, but running) that make biplot more simple and power. All users are free to modify and make it better. Below the function and a small script to learn it. #=============================================================================== # Name : biplot.pca # Author...

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...

Dear R-helpers, Using the package Lattice, I performed a PCA. For example pca.summary <- summary(pc.cr <- princomp(USArrests, cor = TRUE)) The Output of "pca.summary" looks as follows: Importance of components: Comp.1 Comp.2 Comp.3 Comp.4 Standard deviation 1.5748783 0.9948694 0.5971291 0.41644938 Pr...

Hi all, I am doing bootstrap on a distance matrix, in which samples have been drawn with replacement. After that I do PCA on a resulted matrix, and these 2 steps are repeated 1000 times. pca(x) is a vector where I wanted to store all 1000 PCAs; and x is from 1 to 1000 SampleD is a new matrix after resampling; I am getting the following error message, which I don't understand: .... +pca(x)<-princomp(SampleD[...

Hi R-community, I am doing a PCA and I need plots for different combinations of axes (e.g., PC1 vs PC3, and PC2 vs PC3) with the arrows indicating the loadings of each variables. What I need is exactly what I get using biplot (pca.object) but for other axes. I have plotted PC2 and 3 using the scores of the cases, but I don't...

Dear R users, i would like to apply a PCA on image data for data reduction. The image data is available as three matrices for the RGB values. At the moment i use x <- data.frame(R,G,B)#convert image data to data frame pca<-princomp(x,retx = TRUE) This is working so far. >From this results then i want to create a new matrix fr...

Cordial saludo adjunto la base de datos y el script: eu60<- read.csv(file.choose(), header=T, sep=";", dec=".", row.names=1) eu60.pca <- PCA(eu60, quali.sup=19) eu60.data <- cbind.data.frame(eu60[,19], eu60.pca$ind$coord) eu60.ellipse <- coord.ellipse(eu60.data, bary=TRUE) plot.PCA(ellipse=eu60.ellipse, cex=0.8) El 4 de diciembre de 2013 17:35, Camilo Calle <camicalle en gmail.com>escribió: > Muchas gracias...

After doing a PCA using princomp, how do you view how much each component contributes to variance in the dataset. I'm still quite new to the theory of PCA - I have a little idea about eigenvectors and eigenvalues (these determine the variance explained?). Are the eigenvalues related to loadings in R? Thanks, P...

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 he...

Hello everybody, I Would like to get some help to plot together, Principal Components Analysis (PCA) and clusters. I am handling environmental data from 25 locations spread across 5 different ecosystems.When grouped into 5 clusters, locations from different ecosystems are arranged in the same group. So, I want to plot together PCA and Clusters, in a such way that locations belonging to the same...

...to analyse the columns of the single simulation-runs, i.e. e.g. Simulation[[1]][,1] sth. like that but I cannot address these columns... Can anybody please help? Best, Thomas ############################ CODE ############################ analyse<-read.csv2("C:\\Users\\Thomas\\Desktop\\PCA_Kohle_2007.csv",sep=";") rownames(analyse)<-analyse[,1] analyse<-analyse[,-1] require(tseries) require(fSeries) st_rendite<-apply(apply(analyse,2,log),2,diff)*100 pca<-princomp(st_rendite) summary(pca) summary(pca)$loadings screeplot(pca,type="l",main="Scr...

Hello, I'm using the R package called mvpart, which is about the multivariate regression trees. The function I wrote is: mrt1<- mvpart(coefmat~sChip+sScreen+sMem,data=mixdata, xv="pick", plot.add=TRUE,uniform=TRUE,which=4,all=TRUE,xadj=2,yadj=2,rsq=TRUE,big.pts=TRUE,wgt.ave.pca=TRUE,legend=TRUE,bars=F, pca=TRUE) where "coefmat" is a matrix(of dimension N*K) to store the coefficients of my functional data object; and the predictors in the formula are all vectors of length N. Since I set the option "bars=T" and "pca = T", I get the barplot at...

...elow). Is such a thing possible? My data look like this: food group x y z apple fruit 0.216 -0.112 -0.893 orange fruit 0.814 0.097 0.460 broccoli veg -0.239 0.240 -0.425 banana fruit 0.222 0.968 -0.050 parsnip veg 0.139 0.897 0.378 garlic veg -0.104 0.510 -0.400 pca <- read.table(... p3d<- plot3d(pca$x, pca$y, pca$z, xlab="Component 1", ylab="Component 2", zlab="Component 3", col="blue",box=FALSE, size=5) food.v<-as.vector(pca$food) text3d(pca$x, pca$y, pca$z, food.v, cex=0.9, adj = 1) Many thanks, Leigh [[a...

Hi all, I' m trying to figure out if it is appropriate to do a PCA having only categorical data (not ordinal). I have only find the following quote: One method to find such relationships is to select appropriate variables and to view the data using a method like Principle Components Analysis (PCA) [4]. This approach gives us a clear picture of the data using KL-p...

Hi, I have to construct an ellipse interval region on a PCAbiplot, I have my parameters "a" and "b" and I would apply the formula: draw.ellipse(x, y, a = , b = ) I have done a PCA on my data so I have my scores and loading for the first and second component, but my answer is what I have to choose as X and Y into the formula? if "...

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....

...no longer understand how to do so if I want to use ?principal in 'psych' and any of the GPArotation methods. For example, require(psych) r <- cor(mtcars[,c("am","carb","cyl","disp","drat","gear","hp","mpg")]) pca <- principal(r, nfactors = 8, residuals = T, rotate="none") # or 'varimax' or any other GPArotation supported rotation pca I've turned the 'pca' object and ?principal help page upside down and I still cannot find anything that would resemble a 'scores' valu...

Estimados Al leer este interesante script lo corrí, pero al hacer la elipse me devuelve esa información, no encuentro el porque saludos library(FactoMineR) eu60<- read.csv(file.choose(), header=T, sep=";", dec=".", row.names=1) eu60.pca <- PCA(eu60, quali.sup=19) eu60.data <- cbind.data.frame(eu60[,19], eu60.pca$ind$coord) eu60.ellipse <- coord.ellipse(eu60.data, bary=TRUE) plot.PCA(ellipse=eu60.ellipse, cex=0.8) #devuelve esta información Error en plot.PCA(ellipse = eu60.ellipse, cex = 0.8) : el argumento...

I am trying to run PCA on a matrix (the first column and row are headers). There are several cells with NA's. When I run PCA with the following code: ______________________________________ setwd("I:/PCA") AsianProp<-read.csv("Matrix.csv", sep=",", header=T, row.names=1) attach(Asian...

Hi all I have produced a biplot for a PCA (see attached pdf) that I ran however the names of the variables which are placed at the end of the arrows overlap and are thus unreadable. Similarly some of the numbered points overlap. I was wondering if there was a way to edit the biplot to move the label names and if not what the best alternati...