similar to: How to: Compare Two dendrograms (Hierarchical Clusterings) ?

Dear all, I am using the heatmap representations of latticeExtra package and I would be interested to draw color side bars representing the groups of a factor of interest. From my understanding of : > help(dendrogramGrob) ... The 'add' argument can be used for additional annotation at the base of the dendrogram. It should be a list with one component for each row,

Here is my smb.conf: [/usr/local/samba/var] # cat /etc/config/smb.conf [global] client schannel = false server schannel = false client ipc signing = false client signing = false server signing = false winbind sealed pipes = false require strong key = false passdb backend = smbpasswd workgroup = HC1 security = ADS server string = encrypt passwords = Yes username level = 0 map to guest = Bad User

Hi list, This is my domain enviroment and all DC are windows 2008r2 http://i.imgur.com/8cNOtm2.jpeg When I used samba-4.0.5, I join my box to domain "HC1" , I got trusted domain "CHILD2" in "wbinfo -m". [/share/Public] # wbinfo -m BUILTIN MYBOX HC1 CHILD1 TREEROOT HC2 CHILD2 Then I upgraded my box to samba-4.4.4, I lost CHILD2 in "wbinfo -m".

I'm trying to replicate a time-series cross-sectional analysis (countries over years) with SEs clustered by country. ?The original analysis was done in Stata 10 with: xtreg [DV] [IVs] fe cluster(country). Using plm() in R (cran.r-project.org/web/packages/plm/index.html), I've replicated the coefficients. I sought to estimate country-clustered SEs with vcovHC(), and tried a variety of

Note that cophenetic.default (which works on the output of hclust(dist(X))) uses the row names of X as labels. as.dendrogram.hclust does not retain those row names so cophenetic.dendrogram cannot use them (so it orders them based on the topology of the dendrogram). Bill Dunlap TIBCO Software wdunlap tibco.com On Thu, Apr 21, 2016 at 7:59 AM, William Dunlap <wdunlap at tibco.com> wrote:

Hello, I have been using the "cophenetic" function for objects of class "dendrogram" and I have realised that it gives different results when it is used with objects of class "hclust". For instance, running the first example in the help file of the "cophenetic" function, d1 <- dist(USArrests) hc <- hclust(d1, "ave") d2 <-

I've written the function below to simulate the mean 1st through nth nearest neighbor distances for a random spatial pattern using the functions nndist() and runifpoint() from spatsat. It works, but runs relatively slowly - would appreciate suggestions on how to speed up this function. Thanks. --Dale library(spatstat) sim.nth.mdist <- function(nth,nsim) { D <- matrix(ncol=nth,

Thanks Mike. My data has longitude and latitude coords and I used distAB {clim.pact} then mst {ape} to calculate my minimum spanning tree. The nodes are telecoms sites from all over Australia. My goal is to determine the minimum cost of linking them via cabling, and I'm starting by calculating the distance "as the crow flies", but will probably eventually need to calculate the

Hello, how can I get the similarity value (i.e., the inner cluster similarity) that was used to cut a hierarchical tree at a specific height? I would appreciate your help! Best regards, Madeleine

Hello, I've been trying to figure out how to access the individual elements from an object of class phylo. I am reading in 201 trees created by paup as below. > read.nexus("A_30knj_200t.txt", tree.names= NULL) -> anj30 > anj30[1] $tree1 $edge [,1] [,2] [1,] "-1" "-2" [2,] "-2" "-3" [3,] "-3" "1"

Hello, I analyse some free-sorting data so I use hierarchical clustering. I want to compare my proximity matrix with the tree representation to evalute the fitting. (stress, cophenetic correlation (pearson's correlation)...) "The cophenetic similarity of two objects a and b is defined as the similarity level at wich objects a and b become members of the same cluster during the course of

Hi list, This is my domain enviroment and all DC are windows 2008r2 http://i.imgur.com/8cNOtm2.jpeg When I used samba-4.0.5, I join my box to domain "HC1" , I got trusted domain "CHILD2" in "wbinfo -m". [/share/Public] # wbinfo -m BUILTIN MYBOX HC1 CHILD1 TREEROOT HC2 CHILD2 Then I upgraded my box to samba-4.4.4, I lost CHILD2 in "wbinfo -m".

Is there a function available in R that implements Mojena's Upper Tail Rule or that draws a Mojena plot? I would also like to find a function that implements Duda and Hart's stopping rule. Finally with function cophenet how can I achieve a straightforward Cophenet correlation coefficient (i.e. one number for example 0.876) that gives the agreement between the structure of the

Dear R user, I am a biochemist/bioinformatician, at the moment working on protein clusterings by conformation similarity. I only started seriously working with R about a couple of months ago. I have been able so far to read my way through tutorials and set-up my hierarchical clusterings. My problem is that I cannot find a way to obtain information on the rooting of specific nodes, i.e. of

Dear All, I wrote a function for cluster analysis to compute cophenetic correlations between dissimilarity matrices (using the VEGAN library) and cluster analyses of every possible clustering algorithm (SEE ATTACHED) http://old.nabble.com/file/p26288610/cor.coef.R cor.coef.R . As it is now, it is extremely long, and for the future I was hoping to find a more efficient way of doing this sort of

Hi everyone, I'm sure this is pretty basic but I couldn't find a clear example of how to do this. I'm running a regression, say: reg <- lm(Y ~ x1 + year) where x1 is a continuous variable and year is a factor with various year levels. Individually, each year factor variable is not significant, but I have a suspicion they are jointly significant. I can't figure out how to run

I would like to perform partial mantel tests on only within group values, with "between group" values assigned to NA. This is possible in package ncf partial.mantel.test, however this sues a different permutation to that used in ecodist.ecodist will not accept data with NA values, returning a "matrix is not square error. is it possible to perform this test in ecodist? many thanks

I would like to be able to exert certain types of control over the plotting of dendrograms (representing hierarchical clusterings) that I think is best achieved by modifying the dendrogram object prior to plotting. I am using the "dendrogram" class and associated methods. Define the cluster number of each cluster formed as the corresponding row of the merge object. So, if you are

I'd like to get a measure of goodness of fit for a heirarchical clustering result from hclust. Something that would indicate the extent to which the dendrogram accurately represents the original dissimilarity matrix. Is there an easy way to do this? Or, does anyone have code for computing distances between nodes given an hclust structure? So far, my searches have come up dry. -- David

> Background: > OS: Linux Ubuntu Dapper > release: R 2.3.0 > editor: GNU Emacs 21.4.1 > front-end: ESS 5.2.3 > ----------------------------- > Colleagues > I have two spatial datasets (latitude, longitude, fish eggs) and (latitude, longitude, fish larvae) at the same 280 stations (i.e. 280 cases). I want to determine if the 2 datasets are spatially correlated. In other