similar to: Weighted principal components analysis?

Dear R gurus, I have some climatic data for a region of the world. They are monthly averages 1950 -2000 of precipitation (12 months), minimum temperature (12 months), maximum temperature (12 months). I have scaled them to 2 km x 2km cells, and I have around 75,000 cells. I need to feed them into a statistical model as co-variates, to use them to predict a response variable. The climatic

Is it possible to make disappear the id numbers from scatter.dudi (mc analysis) ? a <- as.factor(c(1, 2, 3, 2, 1)) b <- as.factor(c(3, 2, 3, 1, 1)) x <- as.factor(c(1, 2, 2, 1, 3)) y <- as.factor(c(2, 2, 3, 1, 1)) dat <- data.frame(a=a, b=b,x=x,y=y) summary(dat) dat require(ade4) dat.acm <- dudi.acm(dat, scann = FALSE, nf = 2) scatter.dudi(dat.acm) Thank you very much !

Hi, I misunderstand the definition of Canberra distance in R. On Internet and in function description pages of dist() from stats and Dist() from amap, Canberra distance between vectors x and y, d(x,y), is : d(x,y) = sum(abs(x-y)/(x+y)) But in use, through simple examples, we find that the formula is : d(x,y) = (NZ + 1)/NZ * sum(abs(x-y)/(x+y)) with NZ = nb of pairs of coordinates that are

Hello, I am trying to run a PCA in R and I cannot get the PC scores for each of the values. Using pcX <- princomp(X) then loadings(pcX) I can get a listing of the eigenvectors but not the actual PC scores for each value in the dataset. I greatly appreciate any help anyone can offer Thanks Ken

Hi all: How can I calculate the cumulative variance (or variance for each component) in correspondence analysis? If were possible in ADE4 package Thank you -- Antonio Punzón Merino O__---- Instituto Español de Oceanografía c/ /'_ --- Centro Oceanográfico de Santander (*) \(*) -- Promontorio de San Martín S/N ~~~~~~~~~~ 39004-Santander; Spain PO BOX: 240 Tlf: +34 942 29 10 60 Fax: +34

Hi all, I've been trying to figure out how to superimpose a histogram on a biplot that shows the relative contribution of each axis. I have been using the NIPALS function (http://biomserv.univ-lyon1.fr/~dray/ files/softwares/nipals.R) to run principal component analyses. Here is a toy example. source("http://biomserv.univ-lyon1.fr/~dray/files/softwares/nipals.R")

Dear R-users How can I get the eigenvalues out of an lda analysis? thanks a lot christoph -- Christoph Lehmann <christoph.lehmann at gmx.ch>

Dear all, I would like to compute power of a square non symmetric matrix. This is a part of a simulation study. Matrices are quite large (e.g., 900 by 900), and contains many 0 (more than 99 %). I have try the function mtx.exp of the Biodem package: library(Biodem) m <- matrix(0, 900, 900) i <- sample(1:900, 3000, replace = T) j <- sample(1:900, 3000, replace = T) for(x in 1:3000)

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

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Please could someone point me in the right direction as I appear to be having a total mental block with fairly basic PCA problem! I have a large dataframe where rows represent independent observations and columns are variables. I am wanting to perform PCA sequentially on blocks of nrows at a time and produce a graphical output of the loadings for the first 2 EOFs for each variable. I'm sure

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Dear All, I have a set of environental maps and presence-only points for some species. How can I generate distributions models on R using these presence-only data? What packages and functions can I use to do so? Kind regards, Miltinho Brazil [[alternative HTML version deleted]]

Hi, i'm having trouble using Statis in ADE4 package. I want to study a matrix with 18x414...could any body help me?!?!' Urgent Thanks Miguel Ribeiro Portugal [[alternative HTML version deleted]]

Hello I'm using the package ade4 to obtain classification from a .txt file. I use the following commands: cronquist <- read.table("cronquist.txt", h = T, row.names = 8) cronquist <- as.taxo(cronquist[7:1]) cro.phy <- taxo2phylog(cronquist) in which cronquist.txt is a file with a classification of 218 genus of tree species from french Guiana. We I try to use the

I am seeking information on whether anyone has written code to perform Horn's parallel analysis (a procedure that informs the selection of the proper number of components in PCA) in R. Thank you in advance for any help you can provide. Please respond off-list at the email address below. Karen Douglas ******************************************************************* Karen Douglas,

Hi everyone, I am relatively new to R, and I need to perform the principal components analysis of a data matrix. I know that there are a bunch of methods to do it (dudi.pca, princomp, prcomp...) but I have not managed to find a method that can return the residuals obtained by retaining X principal components of the original data, as this MATLAB function can do: http://is.gd/6WeUFF Suggestions?

Hello, I have a problem with the princomp method, it seems stupid but I don't know how to handle it. I have a dataset with some regular data and some outliers. I want to calculate a PCA on the regular data and get the scores for all data, including the outliers. Is this possible on R? Thank you for helping!!! -- View this message in context:

Hello, I am trying to print a table with numbers all rounded to the same number of digits (one after the decimal), but R seems to want to not print ".0" for integers. I can go in and fix it one number at a time, but I'd like to understand the principle. Here's an example of the code. The problem is the 13th element, 21 or 21.0: >nvb_deaths <- round(ss[,10]/100,digits=1)

Dear All, I am using the scatter.dudi finction in the 'ade4' package to produce correspondence analysis (nice) plots. I do not seem to figure out how to plot the raw coordinates only -- or column coordinates only. I would appreciate any help in doing that. Here is the example I am following -- from the package. data(banque) > banque.acm <- dudi.acm(banque, scann = FALSE, nf =