search for: dsvdis

Hello Stephen, I am happy that you help me. Thanks a million. It is a good feeling that you confirm my assumption that dsvdis is not able to deal with missing data, because it says me that I am not completely incapable. Okay now I have the problem what to do. I used this function ´cause there is an option to weight columns differently what I haven´t found in other functions. But now I don´t understand why I have to...

...nsi1 1 0 0 1 0 1 0 0 1 0 0 0 1 0 0 0 0 1 0 0 1 All columns are binary coded characters. The Import was done by this Test<-read.table("TestRFemMalBivariat1.csv",header = TRUE, sep = ";") Now I try to perform a similarity analysis with the dsvdis function of the labdsv package with the sorensen-Index. My first question is if all zeros in my table are seen as missing values and if it islike that how can I change without turning zero into other numbers? Secondly I tried to perform the analysis as simple as possible, after changing t...

Hello, I am using Mac OS X on a power book and R 2.5.0 I try to extract a diagonal from a dissimilarity matrix made with dsvdis, with this code: diag(DiTestRR) But I get this error message: Fehler in array(0, c(n, p)) : 'dim' spezifiziert ein zu großes Array english: Error in array(0, c(n, p)) : 'dim' specifies a too big array. Is there a limit to extract diagonals? I hope somebody will help me! Gree...

Hi, I need to run a PCoA (PCO) for a data set wich has both positive and negative values for variables. I  could not find any distancecoefficient other than euclidean distace running for the data set. Are there any other coefficient works with negtive values.Also I cannot get summary out put (the eigen values) for PCO as for PCA.   Thanks. Dilshan [[alternative HTML version deleted]]

Hi there, I would like to find a more efficient way of permuting the rows and columns of a symmetrical matrix that represents ecological or actual distances between objects in space. The permutation is of the type used in a Mantel test. Specifically, the permutation has to accomplish something like this: Original matrix addresses: a11 a12 a13 a21 a22 a23 a31 a32 a33 Example

Dear mailing group, I have loaded an Excel file into R by calling it ".csv" and using the "read.csv" function in R. However then I want to use the (limma package specific, I believe) function "hclust", which clusters data in a tree dendrogram, by similarity. However, I receive the errors msg.s: 1) "missing observations in cov/cor" 2) "In

Hi; I am working with the similarity matrix below and I would like to plot a two-dimensional MDS solution such as each point in the plot has a label. This is what I did: data <- read.table('c:/multivariate/mds/colour.txt',header=FALSE) similarity <- as.dist(data) distance <- 1-similarity result.nmds <- nmds(distance) plot(result.nmds) (nmds and plot.nmds as defined at