similar to: Clustering in R

Hello, here is my problem, After looking at the mail archives, I found a description of the error I get when I use this package. At first I even tought that they were showing how to solve it. But the thing is that by saying "the programmer forgot drop=FALSE" doesn't show me how I should get rid of the problem I have looked inside the package very quickly and I found three

Hello list, I have two vectors x and x2: x=runif(10) x2=runif(10) and one vectors with their names : my.names=c("x","x2") I would like to cbind these two vectors using their names contained in the vector my.names. I can create a string with comma ncomma=paste(my.names,collapse=",") and now, I just need a function to transform this string into a adequate

Hello, suppose I have a list with matrices: a=list(x1=matrix(rnorm(10),5,2),x2=matrix(rnorm(10),5,2),x3=matrix(rnorm(10),5,2)) I want to compute for all combination of xi and xj (x1,x2 x1,x3 and x2,x3) a value. This value is given for the pair x1,x2 by trace(x1%*%t(x1)%*%x2%*%t(x2)) / trace(x1%*%t(x1))*trace(x2%*%t(x2)) I know that product matrices t(xi)%*%xi can be obtained by:

Hello, I have a question that is not directly related to R ... but I try to do it in R ;-) : I would like to generate a matrix Q satisfying (for a given Z, X and W) the two following conditions: t(Q)%*%Q=Z (1) XQ=W (2) where: Q is m rows and r columns X is p rows and m columns D is p rows and r columns C is r rows and r columns with m>p,r e.g: m=6, p=2 r=3

Hello list, Sorry, these questions are not directly linked to R. If I consider an indefinte real matrix, I would like to know if the symmetry of the matrix is sufficient to say that their eigenvectors are real ? And what is the conditions to ensure that eigenvectors are real in the case of an asymmetric matrix (if some conditions exist)? Thanks in Advance, St?phane DRAY

I am not sure a previous e-mail reached the list (no mail aknowledgement from R-boundle etc.). The question was how to write polygon or segment coordinates into a shapefile set or any other ArcGIS supported format. The library shapefiles seems to do something but the documentation is a bit beyond of my mind.... and I cannot get the meaning of the functions write**** and its application to the case

Hello list, I have used scan function to import data into R. I have done some analysis and find strange results. I have found my problem : when importing data with scan, this can slightly modify the data : > write(c(0.251,3.399,-0.481,0.266),"essai.txt") > scan("essai.txt") Read 4 items [1] 0.251 3.399 -0.481 0.266 > print(scan("essai.txt"),17) Read

Hello list, I have 3 matrices with same dimension : > veca=matrix(1:25,5,5) > vecb=matrix(letters[1:25],5,5) > vecc=matrix(LETTERS[1:25],5,5) I would like to obtain a new matrix composed by alternating rows of these different matrices (row 1 of mat 1, row 1 of mat 2, row 1 of mat 3, row 2 of mat 1.....) I have found a solution to do it but it is not very pretty and I wonder if I

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 =

Does R have a function to calculate Bray-Curtis distance measures, which is probably one of the most frequently used and recommended dissimilarity measures in ecology? It isn't mentioned in dist().

Bonjour à tous, Je débute dans l'utilisation de R, et suis à la recherche de toute piste me permettant l'introduction à ce logiciel. J'ai pour le moment la fiche d'Emmanuel Paradis: "R pour les débutants", mais j'aimerais savoir où je peut trouver d'autres documentations notamment pour le traitement statistique de données (Anova, modèle linéaire et modèle

Hello I have some kind of problem with R. I want to do a pca (I work on R and ade4 library) but R doesn't wan to realize my pca because of my data: I have some binary variable (presence/absence of birds, hole, vegetals...) and metric variable (cliff 's size...) and each time I have an error message because of the mix of the 2 type of variable. So, what can I do? Famille SALMON

Does anyone know R is to be cited in a publication? I've looked everywhere on the website and cannot find this. Thanks, Heather -- Heather Maughan Department of Ecology and Evolutionary Biology Biosciences West 310 University of Arizona Tucson, AZ 85701 Phone: 520-626-5108 Fax: 520-621-9190 hmaughan at u.arizona.edu

Hi, I am trying to plot several rows out of a list of thousands. I have 40 columns, and about 16,000 rows with the following Df structure. ID X01 X02 X03..X40 AI456 45 64 23... AI943 14 3 45 .. AI278 78 12 68.. BW768 -2 -7 34.. ... My question is, I have a list of 100 IDs generated elsewhere (Df-"Ofinterest"), I would like to plot the 100 IDs from that data frame over the 40 columns

Hi I'm seeing some "odd" behaviour with cbind(). My code is: > cat <- read.table("cogs_category.txt", sep="\t", header=TRUE, quote=NULL, colClasses="character") > colnames(cat) [1] "Code" "Description" > is.factor(cat$Code) [1] FALSE > is.factor(cat$Description) [1] FALSE > is.factor(rainbow(nrow(cat))) [1]

Hello List, I would like to orthonormalize vectors contained in a matrix X taking into account row weights (matrix diagonal D). ie, I want to obtain Z=XA with t(Z)%*%D%*%Z=diag(1) I can do the Gram-Schmidt orthogonalization with subsequent weighted regressions. I know that in the case of uniform weights, qr can do the trick. I wonder if there is a way to do it in the case of non uniform

Hi Now a more theoretical question. I have two correlation matrices - one of a set of variables under a particular condition, the other of the same set of variables under a different condition. Is there a statistical test I can use to see if these correlation matrices are "different"? Thanks Mick

Hi, Very so often when i am plotting something, doing a histogram, or whatever i am struggling to find out which are the numbers for different colors, palette names, types of lines, symbols, etc. Is there any documentation on line with all these numbers / names and the associated symbol / color??? For example if i am using the command image it uses a palette from red to yellow, with red the

I'm doing some analyses of historical data from France in 1830 on 'moral statistics' that I'd like to show on a map. I've done most of my analyses in SAS, but a few things would work better in R. To do this, I have to adjust the modern map, library(maps) map('france') to adjust for changes in departments (86 in 1830, to 97 now). I've read the documentation

May be a simple question, but not understanding why in princomp I get different results for loadings and summary for my eigenvectors and eigenvalues. When I use pc.cr$loadings using the USArrests dataset the proportion of variance is equal for each of the components, but when summary(pc.cr) is used the proportion of variance is showing different proportions. My question is why do they differ? I