similar to: Distance matrix from a binary data frame

Hi, I am trying to calculate a distance matrix on a binary data frame using dist.binary() {ade4}. This is the code I run and the error I get: > sjlc.dist <- dist.binary(as.data.frame(data), method=2) #D = (a+d) / (a+b+c+d) Error in if (any(df < 0)) stop("non negative value expected in df") : missing value where TRUE/FALSE needed I don't know if the problem are the

I'm trying to perform a mantel test that ignores specific pairs in my distance matrices. The reasoning is that some geographic distances below a certain threshold suffer from spatial autocorrelation, or perhaps ecological relationships become less relevant that stochastic processes above a certain threshold. The problem is that I can't find a way to do it. If I replace values in either or

I would like to randomly shuffle a distance object, such as the one created by ade4{dist.binary} below. My first attempt, using sample(jc.dist) creates a shuffled vector, losing the lower triangular structure of the distance object. How can I Ishuffle the lower triangular part of a distance matrix without losing the structure? Thanks. --Dale x1 <- c(rep(0,4),1) x2 <- c(rep(0,2),rep(1,3))

Hi, I have the following function that I want to apply to a list of 14 matrices (1536 x 170) of binary data: DRes <- function(x, nr = 10000, metric = "mixed", ...) { require(analogue) require(ade4) m <- c() for (i in 1:nr) { set.seed(i) x1 <- x[, sample(dimnames(x)[[2]], length(x[1,])/2)] x2 <- x[, !dimnames(x)[[2]] %in% dimnames(x1)[[2]]] d1 <-

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

hi, I am trying to calculate distance matrices for binary data frame. I am using dist.binary in 'ade4' package. This is the code i run and get error message as 'missing value where True/False needed: clss <- as.data.frame(cls) dist.binary(clss, method = 1, diag = FALSE, upper = FALSE) Also, if i convert the factors into numeric(i.e,1&2 in the place of 0&1 for present/absent

Dear, I have a data frame object (FSTc) which is in fact a matrix of class data.frame but created from a txt file using the command FSTc<-read.table("FSTcmatrix.txt", header=T) I would like to transform it in a distance matrix of class dist to use it with the ade4 package. I'm quite sure this is a simple operation but i just don't have the commands. Could anyone help?

Dear R users I wondered if any of you ever tried to calculate distance matrix with very large data set, and if anyone out there can confirm this error message I got actually mean that my data is too large for this task. negative length vectors are not allowed My data size and code used dim(mydata_nor)[1] 365000 144> d <- dist(mydata_nor, method = "euclidean") Here my

Hi there I have been using R to perform kmeans on a dataset. The data is fed in using read.table and then a matrix (x) is created i.e: [ mat <- matrix(0, nlevels(DF$V1), nlevels(DF$V2), dimnames = list(levels(DF$V1), levels(DF$V2))) mat[cbind(DF$V1, DF$V2)] <- DF$V3 This matrix is then taken and a distance matrix (y) created using dist() before performing the kmeans clustering. My query

Hi useRs, I am trying to compare several distance matrices obtained from subsets of variables from the same experiment. I put all the subsets in a list and then calculated the distance matrices with lapply. In order to do a mantel test between them I wrote a function the returns a list with the output of single tests. I would like to include the name of the tests, so I know what each element

Hi all, I am trying to compare two distance matrices with R. I would like to create a XY plot of these matrices and do some linear regression on it. But, I am a bit new to R, so i have a few questions (I searched in the documentation with no success). The first problem is loading a distance matrix into R. This matrix is the output of a the Phylip program Protdist and lookes like this: 5

Dear all: I want to ask question about "binary" distance measure. As far as I know, there are many binary distance measures,eg, binary Jarcad distance, binary euclidean distance, and binary Bray-Curtis distance,etc. It is even more confusing because many have more than one name. So , I wan to know what the definite name of the binary distance measure of the "dist" function

Hello, Im working on a 50933 point count bird abundance dataset. I've succeeded in calculating a distance matrix for this entire set, but I don't have sufficient memory to convert this to a matrix, as below... abun.dist <- dist(abun.mat[1:50993,1:235) test <- rowMeans(as.matrix(abun.dist)) Error in matrix(0, size, size) : too many elements specified ive been able to run a hclust()

Use something like hclust(as.dist(mydist), ...) ought to work. Andy -----Original Message----- From: r-help-bounces at stat.math.ethz.ch [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of ucecgxu at ucl.ac.uk Sent: Wednesday, January 18, 2006 4:47 PM To: r-help at stat.math.ethz.ch Subject: [R] r-help, how can i use my own distance matrix without using dist() Dear R-helpers, i am a

Dear UseRs, i want to apply mantel test by comparing a list of 124 distance matrices with a reference distance matrix "q". The list of distance matrices was created by the following command.. u<-lapply(el, function(x) dist(x)) where "el" is a data frame of 75 columns and 124 rows. Therefore, the list of distances matrices, made out of it should have 75 elements each

Hello R users, Can any one please help me to find a way to build phylogenetic tree by R program from any distance matrix. Suppose I have a data like : MATRIX [1] '1' 0.0 [2] '2' 0.071 0.0 [3] '3' 0.036 0.286 0.0 [4] '4' 0.429 0.75 0.714 0.0 [5] '5' 0.679 0.179 0.214 0.536 0.0 [6] '6' 0.893 0.929 0.964 0.464 0.357 0.0 [7]

Dear all, below you find enclosed my message from January 9th and my program (attention: beginner). Thanks for both answers! a. However, as far as I know the cosine is not the same as the Pearson correlation (only in special cases). b. Reid Huntsinger's hint was very useful, however I had to transpose the matrix first, for I want to calculate the distance of the _rows_. Regards, Petra

Dear R-helpers, i am a beginner of R and i am using cluster package to do hierarchical clustering i am wondering if i can use my own distance matrix to do the hierarchical clustering without using dist() function. if i have my own distance matrix, how can i ask hclust() function to recongnize it( as the output of dist() function). thank you very much and i looking forward to hearing from you.

heatmap.2 defaults to dist for calculating the distance matrix and hclust for clustering. Does anyone now how I can set dist to use the euclidean method and hclust to use the centroid method? I provided a compilable sample code bellow. I tried: distfun = dist(method = "euclidean"), but that doesn't work. Any ideas? library("gplots") library("RColorBrewer") test

Hi All, I'm working on analyzing a large data set, lets asume that dim(Data)=c(1000,8700). I want to calculate the canberra distance between the columns of this matrix, and using a toy example ('test' is a matrix filled with random numbers 0-1): > system.time(d<-as.matrix(dist(t(test), method = "canberra", diag = FALSE, upper = FALSE, p = 2))) user system