similar to: p-values with pvclust

Hi, I am new to clustering and was wondering why pvclust using "maximum" as distance measure nearly always results in p-values above 95%. I wrote an example programme which demonstrates this effect. I uploaded a PDF showing the results Here is the code which produces the PDF file: ------------------------------------------------------------------------------------- s <-

Hi all I am writing to you with a question regarding the pvclust package. And yes, before the usual people produce their usual contact-the-package-maintainers line, ye, I tried that but the emails one can find on the web either bounce or are not responded to. Also, yes, this error has already been reported as a bug but been shot down as not reproducible

Hello all, I posted a question to this list last week and received no response. I am unsure if this means no-one knows the answer or if I posed the question badly. I'm going to assume I posed the question badly and try again. I am new to R so it is quite likely it's a very naive question, however if there is something blindingly obvious that I am missing or if there is another resource I

Hi all I am trying to perform the follwing: fit<-pvclust(wq, method.hclust="ward", method.dist="euclidean") but get a strange error message that I just cant figure out. Has anyone come across this? Any help would be most appricieated Error in hclust(distance, method = method.hclust) : NA/NaN/Inf in foreign function call (arg 11) In addition: Warning message: NAs

Hi all, I'm new to R and I'm struggling to decipher an error message. Briefly, I am trying to use the pvclust package to do hierarchical clustering of some CGH data. The data is from the Progenetix CGH database. It is arranged as a table where each column is a single case and each row is a single chromosome band. The value in each cell is either 0, 1, 2, or -1. Corresponding to no change,

Dear All I'm using PVClust to perform hierarchical clustering, for the output plot I can control most of the graphical I need, however the plot is large and I would like to split it vertically into two panels one above the other. Is there a way to plot only part of a PVClust plot, I tried to convert it to a dendrogram with result2 = as.dendrogram(result) however I get the error message

Is there a way to assign color to nodes as with hclust/as.dendrogram/dendrapply when using pvclust? The problem is that as.dendrogram isn't working on the pvclust objects. library(pvclust) pvc <- pvclust(matrix, nboot=1000) plot(pvc) -- View this message in context: http://www.nabble.com/Node-colors-in-pvclust-tp24405329p24405329.html Sent from the R help mailing list archive at

You should reply to the list, not just me, and even more because I cannot really help you!! My guess (but I don't know this package, and even less this function) is that pvclust() is expecting a matrix as the first argument. However, "cluster" is no data, it is a function. Why, I don't know. Take a closer look at ?pvclust, especially the "usage",

I realize questions about packages should go to the package maintainer, but perhaps I have an old email address (suzuki3 at is.titech.ac.jp) Also I have both a general, and a specific, question. 1) General question: i've used pvclust before to assess significance of clusters and got reasonable results. However, on a new data set (see below) the results seem odd. I wonder if pvclust is a

Hello, I am attempting to assign significance levels to a UPGMA cluster analysis as part my doctoral research. The pvclust function works well but doesn't include the similarity index I need (morisita's) as an option for computing a distance matrix. Morisita's is available in vegdist in the VEGAN library but I am having a hard time getting the vegdist function to "direct

Dear List, I have another question to bother you about how to do clustering. My data consists of 49 columns (49 variables) and 238804 rows. I would like to do hierarchical clustering (unsupervised clustering and PCA). So far I tried pvclust (www.is.titech.ac.jp/~shimo/prog/*pvclust* /) but I always had the problem like for R like "cannot allocate the memory". I am curious about what

Good morning, I am analyzing a dataset composed by 364 subjects and 13 binary variables (0,1 = absence,presence). I am testing possible association (co-presence) of my variables. To do this, I was trying with cluster analysis. My main interest is to check for the significance of the obtained clusters. First, I tried with the pvclust() function, by using method.hclust="ward" and

Hi there, I have been trying to use the "pvclust" package but have been having some difficulties. This is the first time I have used R so I am sure the mistake I am making is a basic one. The data I have is a distance matrix and I have been using the command; fit <- pvclust(cluster, nboot=1000, method.dist="euclidean") to try and perform hierarchical clustering with

Hello there, Here's a question regarding p-values on clusters produced by hierarchical cluster analysis. A web search led me to the program pvclust to tackle this problem. But when I run the problem I get strange results. The 'AU' (approximately unbiased) p-values are very different from the 'BP' values (ordinary boot-strap) p-values. The AUs commonly are in the 80-100

Hi, I have a microarray dataset of dimension 25000x30 and try to clustering using hclust(). But the clustering on the rows failed due to the size: > y<-hclust(dist(data),method='average') Error: cannot allocate vector of size 1.9 Gb I tried to increase the memory using memory.limit(size=3000), still got the same error. I also tried agnes() from cluster package and pvclust() from

Hi R users,   I am doing multiscale bootstrapping for clustering through pvclust package. I have large data set (observations 182 and variables 5546). When i tried to make bootstrapping, then i got message as "Bootstrap (r = 0.5)............Error: cannot allocate vector of size 117.3 Mb". I am new R user and could not understand what is the problem and also don't know the easiet

Buen día, no sé si estoy utilizando bien la lista, es la primera vez. Si lo hago mal me corrigen por favor. Sobre tu comentario Pedro, muchas gracias. Lo qeu entiendo con tu sugerencia de set.seed es qeu de esa forma fijas los resultados, pero no estoy seguro si otra agrupación funcione mejor. Es decir me interesa un método de agrupación que genere la "mejor" agrupación y como los

I want to be able to create one menu object that has fields_for :brunch, :lunch, and :dinner. The menu object has_many brunches, lunches, and dinners, but each time I "edit", only one brunch, one lunch, and one dinner object are added. I''m using carrierwave to upload brunch_menus, lunch_menus, and dinner_menus (attributes of brunches, lunches, and dinners respectively) as

I want to classify bipolar neurons in human cochleas and have data of the following structure: Vol_Nuc Vol_Soma 1 186.23 731.96 2 204.58 4370.96 3 539.98 7344.86 4 477.71 6939.28 5 421.22 5588.53 6 276.61 1017.05 7 392.28 6392.32 8 424.43 6190.13 9 256.41 3850.51 10 249.17 3118.14 11 276.97 3037.29 12 295.30 3703.76 13 314.43 5265.97 14 301.15 5781.73 I

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