similar to: All possible combinations of functions within a function

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 <-

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'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

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 List Members, I have created a function to run a simulation based on a given set of values within a vector, such that I run the function like this: new.data<-sapply(vector, function) In which I run 'function' on every value within a vector that I created. The result is a matrix of 1000 rows, and as many columns as the length of the vector. I modified the function to utilize

I know that within sum of squares, DB, sillhouette and cophenetic are indicators of clustering quality, but what indicators I need to observe when I choose attributes for kmeans? -- View this message in context: http://r.789695.n4.nabble.com/Feature-selection-for-kmeans-tp4657830.html Sent from the R help mailing list archive at Nabble.com.

I think the results differ only in the order of the labels. The following function puts the labels in a standard order and then the results are the same: canonicalize.dist <- function (distObject) { o <- order(labels(distObject)) as.matrix(distObject)[o, o, drop = FALSE] } identical(canonicalize.dist(d2), canonicalize.dist(d3)) [1] TRUE Bill Dunlap TIBCO Software

Hello all, I wish to compare two dendrograms (representing Hierarchical Clusterings). My problems are several: 1) how do I manually create a dendrogram object ? That is, how can I reconstruct it as an "hclust" object that creates such a dendrogram, when all I have is the dendrogram image (but don't have the underlaying distance matrix that produced it) ? I see that there is a

Hi List, I am looking for a variable selection procedure with a forward-backward selection method. Firstly, it is meant to work with the cophenetic correlation coefficient (CPCC) and intended to find the variable combination with the highest cophenetic correlation. Secondly, it is aimed at Gower metric with wards method (though this could be easily extended) aimed at categorical data. What I

Dear All, I am trying to fill in a blank vector ("a") with one value at a time, with the value of the number of rows in a randomized dataset with rowSums=0. Below is the code I've got so far, but what I want to be as the last line is " a[1st NA,]=nz" such that this will run until all of my NAs are replaced with an integer value based on randomizations.

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

---------- Forwarded message ---------- From: <r-help-owner@r-project.org> Date: 2013/2/8 Subject: vegdist Error en double(N * (N - 1)/2) : tama?o del vector especificado es muy grande To: caro.bello58@gmail.com Message rejected by filter rule match ---------- Mensaje reenviado ---------- From: caro bello <caro.bello58@gmail.com> To: r-help@r-project.org Cc: Date: Fri, 8 Feb 2013

Hi! Thanks for providing great help in R-related statistics. Now, however I'm stuck. I'm not a statistics person but I was recommended to use R to perform a nmds plot and PerMANOVA of my dataset. Sample(treatment) in the columns and species (OTU) in the rows. I have 4 treatments (Ambient Temperature, Ambient temperature+Low pH, High temperature, High temperature+low pH), and I have 16

Dear all, I am trying to get a PERMANOVA with quite large data set. I am reading a lot about this question, but I do not get the answer about it. Although I know that the R function is adonis () (vegan package), it does not work: adonis(Pha.env~SPha, data=Pha, permutations=10) The error message: Error: cannot allocate vector of size 334.2 Mb In addition: Warning messages: 1: In vegdist(lhs,

hello, i'd be happy if someone could provide help with the following problem: i have a dist.matrix that comes from vegdist() function of the vegan package. the used method = "horn" is not accepted as argument in hvcluster(...,dist.method="..."). is there a way to incorporate the method "horn" in hvcluster()? thanks in advance! yours, kay -- View this

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]]

Hello I have 2 rows in a matrix and I want to calculate the Gower Distance between the 2 , how can I do it? I searched and found nothing that can help me, and my program doesn't know the gdist function and I couldn't find it on the R help site. Can anyone help me plz Thank u all [[alternative HTML version deleted]]

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

Dear All, I would like to use the simprof function (clustsig package) but the available distances do not include Jaccard distance, which is the most appropriate for pres/abs community data. Here is the core of the function: > simprof function (data, num.expected = 1000, num.simulated = 999, method.cluster = "average", method.distance = "euclidean", method.transform =