similar to: Visualizing a dissimilarity matrix in Euclidean space

Hello, this morning I apparently had tinc crash on me. In 2 independent tinc clusters of 3 nodes each (but located in the same datacenter), one tinc process crashed in each of the clusters. One process apparently with `status=6/ABRT`, the other with `status=11/SEGV`. Interestingly, they crashed with only 5 minutes difference. The only thing I can come up with that might explain this correlation

Hi all, I'm using a tinc 1.0.19 (from Debian Squeeze) setup with some nodes connecting to a "server" node which has "StrictSubnets = yes". Whenever a new node is added to the mesh, a process generates and drops its host file in the server's host directory before the node is booted and tries to connect. For instance, I create a node "node_2" and a host file

Dear R's! I am strugling with cancor procedure in R. I cannot figure out the meaning of xcoef and of yxcoef. Are these: 1. standardized coefficients 2. structural coefficients 3. something else? I have tried to simulate canonical correlation analysis by checking the eigenstructure of the expression: Sigma_xx %*% Sigma_xy %*% Sigma_yy %*% t(Sigma_xy). The resulting eigenvalues were the same

I'm running samba 2.2.8a on a redhat 9 box, everything works great, but ever since I playd with the system-auth I now have to enter a password in twice when I logon to the console. Any one got any ideas ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Iwan Davies Server Support and Development Technician Cyngor Sir Ceredigion County Council IT Section Finance iwandav@ceredigion.gov.uk

Dear Users, I am a new user of the sem package. I have a model that is being flagged by sem as "S is numerically singular: expect problems" I have checked John Fox's response to a similar problem. Obviously the variance-covariance matrix is singular, but none of the possible reasons seems to hold in my case. Any leads how I could get the model to work? from Prof. John Fox That

NAME rq v2.3.2 SYNOPSIS rq (queue | export RQ_Q=q) mode [mode_args]* [options]* URIS http://raa.ruby-lang.org/project/rq/ http://www.linuxjournal.com/article/7922 DESCRIPTION ruby queue (rq) is a zero-admin zero-configuration tool used to create instant linux clusters. rq requires only a central nfs filesystem in order to manage a simple sqlite database as a distributed

> BDR> You will need to call it something else: dist is a clone of an S > BDR> function, and dist(X, "manhattan") is well-established usage. > > one could still imagine an extra Y argument such that > dist(X, Y=myY, method="euclidean") > and dist(X, "euclidean", Y=myY) > would work > one could even make it such that > both

a <- c(1:10) b <- c(.5, .6, .9, 10, .4, 3, 4, 9, 0, 11) d <- c(21:30) z <- data.frame(a,b,d) library(fields) results <- c() for(i in 1:(length(rownames(z))-1)){ results[i] <- rdist(z[i,], z[(i+1),]) } results.1 <- data.frame(results) f <- rownames(z) r <- f[-1] rownames(results.1) <- r colnames(results.1) <- f[1] this does what I want it to do - is

Dear R-Help-Team, I would like to cluster my data using the ward-method. In several papers I read (e.g. Bahrenberg) that it is neccesary to use the "squared euclidean distance" with the ward-method. Unfortunatelly I cannot find this term in r as a method for measuring the distance. Does anybody have an idea? Thanks in advance, Carolin [[alternative HTML version deleted]]

I am studying on statistical shape analysis, I wonder is there any way or package available that I can perform Euclidean Distance Matrix Analysis (EDMA I or EDMA II) in R... thanks Gokhan -- View this message in context: http://r.789695.n4.nabble.com/Euclidean-Distance-Matrix-Analysis-EDMA-in-R-tp2266797p2266797.html Sent from the R help mailing list archive at Nabble.com.

Hi, I would like to calculate the RELATIVE euclidean distance. Is there a function in R which does it ? (I calculated the abundance of 94 chemical compounds in secretion of several individuals, and I would like to have the chemical distance between 2 individuals as expressed by the relative euclidean distance. Some compounds are in very low abundance whereas others are in high abundance,

> 3x3 subset used > Locus1 Locus2 Locus3 > Samp1 GG <NA> GG > Samp2 AG CA GA > Samp3 AG CA GG > > The euclidean distance function is defined as: sqrt(sum((x_i - y_i)^2)) My > assumption was that the difference between

Hello all, I've been pouring through the various spatial packages, but haven't come across the right thing yet. Given a set of points in 2-d space X, i'm trying to find the subset of points in Y proximate to each point in X. Furthermore, the proximity threshold of each point in X differs (X$threshold). I've constructed this myself already, but it's horrificly slow with a

Dear Users,I have two matrices A=15*365 and B=1*365. i want to calculate "Euclidean Distance" between these matrices in such a way that i should have euclidean distance of matrix B against all the columns of matrix A. More precisely, first i want euclidean dist. of column 1 of A against B, then column 2 against B, 3rd column of A against B and so on.is there a way in r to do it?your help

HISTORY --- 2.3.3: - fixed bug in updater related to io files (see tmp_stdin in jobqueue.rb) - [IMPORTANT] removed feature where stdin jobs could contain comments (''#''). input lines are now taken literally __except__ blank lines, which are still ignored. - added ability to dump stdin/stdout/stderr for any job rq q stdout 42

?for doesn't return anything help.search("for") doesn't return anything- Is the for loop so prevelant in computer programing that the documentation is implicit or is R paradigm to discourage the use of the for loop. I will post data probably tonight, but here is my problem. I have preformed an MDS on a set of data. I have the scores of the four axes that are the optimal

Hi 1. I have two raster files *.asc (identical size) 2. The data in each contain presence or absence data in each cell represented by a 1 or 0 respectively 3. I would like to take the location of each 1 (presence cell) in raster file 1 and measure the euclidean distance to the nearest 1 (presence cell) in raster file 2. Obviously in some cases there will be overlap so the distance will be zero.

I have a program which needs to compute squared Euclidean distance between two vectors million of times, which the Rprof shows is the bottleneck. I wondered if there is any faster way than my own simple function distance2 = function(x1, x2) { temp = x1-x2 sum(temp*temp) } I have searched the R-help archives and can not find anything except when the arguments are matrices. Thanks for any

Dear R-helpers, I need to quantify dissimilarity of two minimum spanning trees, specifically dissimilarity of their topologies. (They connect the same objects but they are calculated from different sets of variables.) Are you aware of any R-function doing this? Best regards Ondrej Mikula

Dear all, My data includes almost three thousand people who rank ten categories into three variables. The simple example below is almost same except I have many missing values. x <- cbind( sample( LETTERS[1:10] , 3000 , replace = TRUE ) , sample( LETTERS[1:10] , 3000 , replace = TRUE ) , sample( LETTERS[1:10] , 3000 , replace = TRUE ) ) I try to figure