similar to: method default for hclust function

I have two indicator variables ABS and DEFF. I want to create another indicator variable which will take value 1 if either ABS=1 or DEFF=1. Otherwise, it will take value 0. How can I make that? [[alternative HTML version deleted]]

I have a huge dataset(15k X 18) and tried to use the heatmap in R to examine the patterns. However, I found that heatmap and heatmap.2 gave me completely different outputs. Here are the codes: ------------ > dim(as.matrix(data.dcpm)) [1] 15462??? 18 > > heatmap(as.matrix(data.dcpm), col=topo.colors(100)) > heatmap.2(as.matrix(data.dcpm), col=topo.colors(100), key=TRUE,

Dear UseRs,i want to find centroid of clusters, which i generated by hclust. Is there a way doing that? i took mean to elements in each cluster to get centroid but i am not sure if i am right? thanks in advanceeliza [[alternative HTML version deleted]]

Dear fellow users Are there any Vietnamese language resources for beginners of R? If so, I would be interested in hearing from people who have had experience with them and which are better (if there is more than one). I am involved with an aid project in Vietnam, and would like to move the scientists involved from using Excel for 'analysis' to R. Thanks .... Peter Alspach The

Hello. I have the following distance matrix between 8 points: [1,] 0.000000 3.162278 7.280110 8.544004 7.071068 9.899495 6.403124 8.062258 [2,] 3.162278 0.000000 5.000000 6.403124 4.472136 8.944272 6.082763 8.062258 [3,] 7.280110 5.000000 0.000000 1.414214 1.000000 5.000000 4.242641 5.830952 [4,] 8.544004 6.403124 1.414214 0.000000 2.236068 4.123106 4.472136 5.656854 [5,] 7.071068 4.472136

I've been trying to get plot.hclust to work with a hclust object I created and have not had much success. It seems that there is some "hidden" characteristic of a hclust object that I can't see. This is most easily seen in the following example, where plot.hclust works on one object, but when this object is "dumped" and then re-read, plot.hclust no longer works. Is

Hi All, Just want to make sure, in function "bclust", do the following argument only have one option? argument "dist.method" has one option "Euclidian"; argument "hclust.method" has one option "average"; argument "base.method" has one option "kmeans". Thank you! [[alternative HTML version deleted]]

Hello all, I'm now working with hclust objects and was hoping to perform some basic editing on them like: - Joining = the merging of two hclust objects (so they will share one root) - Splicing = So to cut/extract a branch out of an hclust object - that by itself will be an hclust object. I noticed I could extract one element of an hclust object by turning it into a dendrogram,

Hello, I would like to cut a hclust tree into several groups at a specific similarity. I assume this can be achieved by specifying the "h" argument with the specified similarity, e.g.: clust<-hclust(dist,"average") cut<-cutree(clust,h=0.65) Now, I would like to draw rectangles around the branches of the dendrogram highlighting the corresponding clusters, as is done by

Having some problems with using hclust.identify on my data, I revert to trying it out on the example in the help manual. My result is still the same (as with my own data): data(iris) hci <- hclust(dist(iris[,1:4])) plot(hci) testx<-identify.hclust(hci) Error in rect.hclust(x, k = k, x = x$x, cluster = cluster[, k - 1], border = "red") : k must be between 2 and 0

Hello, I am using the hclust function to cluster some data. I have two separate files with the same data. The only difference is the order of the data in the file. For some reason, when I run the two files through the hclust function, I get two completely different results. Does anyone know why this is happening? Does the order of the data matter? Thanks, RC -- View this message in

Hello, I'm having trouble figuring out how to see resulting groups (clusters) from my hclust() output. I have a very large matrix of 4371 plots and 29 species, so simply looking at the graph is impossible. There must be a way to 'print' the results to a table that shows which plots were in what group, correct? I've attached the matrix I'm working with (the whole thing

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

Good afternoon, I ran heatmap and hclust on the same matrix x (strictly, I ran heatmap(x), and hclust(dist(t(x))), and realized that the two dendrograms were slightly different, in that the left-right arrangement of one pair of subclusters (columns) was reversed in the two functions (but all individual columns were grouped correctly). Looking through the code for heatmap as a most definite

Hello! I have the following problem. I would like to plot the hclust object "hcd" (bellow, at the end of the mail) with ticks at seq(0.05,0.25,by=0.05). I tried using the code plot(hcd) and plot(hcd,axes=FALSE) axis(2,seq(0.05,0.25,by=0.05)) In both cases, the resoult is the same, ticks at 0.05 and 0.25 are not printed. I tried changing the ylim argumet in plot, however I got a

Dear R users, I have noted a difference in the merge distances given by hclust using centroid method. For the following data: x<-c(1009.9,1012.5,1011.1,1011.8,1009.3,1010.6) and using Euclidean distance, hclust using centroid method gives the following results: > x.dist<-dist(x) > x.aah<-hclust(x.dist,method="centroid") > x.aah$merge [,1] [,2] [1,] -3 -6

dear group members, I am looking for a function that assess the stability of cluster. The result of hclust function is an hclust object which can be plot as a dendrogram. However to have confidence in the tree topology usualy bootstap is applied. I understand that I can apply bootstarp on the original data and then run hclust(dist() ) as much as I resampled but how to comapre the topologies the I

Hi, I have the distance matrix computed and I feed it to hclust function. The plot function produces a dense dendrogram as well. But, the cutree function applied does not produce the desired list. Here is the code x=data.frame(similarity_matrix) colnames(x) = c(source_tags_vec) rownames(x) = c(source_tags_vec) clust_tree=hclust(as.dist(x),method="complete") plot(clust_tree)

Hi, This is a beginner R question. I have a 4x4 matrix named 'lookup' with the following values: 1 2 3 4 1 0.000000 2.828427 5.656854 8.485281 2 2.828427 0.000000 2.828427 5.656854 3 5.656854 2.828427 0.000000 2.828427 4 8.485281 5.656854 2.828427 0.000000 I then create a new empty matrix named 'dd' with specfic row and col names :

Dear group, I am currently struggling with the following problem for a while: I want to create a list whose elements consists of lists themselves. More concise: The list elements are HCLUST objects. However, when I try to append the HCLUST objects to my list via: cluster_list <- append(cluster_list, HCLUSTobject) the HCLUST object is appended - but not as an object but as its components. So