similar to: Cluster and Tree Conversion

Hi I have a problem using the package cluster on my binary data. I want to try mona at first. But i get the an error. hc<-read.table("all.txt", header=TRUE, sep="\t", row.names=1) srt(hc) `data.frame': 51 obs. of 59 variables: $ G1p : int 2 1 1 1 1 1 1 1 1 1 ... $ G1q : int 1 1 1 1 1 1 1 1 1 1 ... $ G2p : int 1 1 1 1 1 1 1 1 1 1 ... $ G2q : int 1 1 1 1 1 1

Hi: I have calculated the Silhouette score and Dunn score after hierarchical clustering for 3 clusters: #Distance measure d <- dist(USArrests, method = "euclidean") #Hierarchical clustering hc <- hclust(dist(USArrests), "ave") #calculating silhouette value for 3 clusters sil<- silhouette(cutree(hc, k=3), d) #calculating Dunn index for 3 clusters clus <- cutree(hc,

Dear R helpers, I am quite new working with R, and that might be a very easy question for some of you. So I hope you can help me!! I used a hirarchical cluster analysis to create dendrograms, like that: hc <- hclust(dist(USArrests), "ave") plot(hc) plot(hc, hang = -1) Here I want to compare the number of bifurcations for each species, but therefor I need this numbers first. There

Hi! I just discovered that cutree() and cut.dendrogram() do not assign the same cluster numberings when called on the same tree. More specifically, cutree() assigns cluster numbers by order of appearance in the data, while cut.dendrogram() sorts clusters by height (see example below). I guess this is for historical reasons? I'm hit by this difference when I want to get a vector of cluster

This worked for me with your example: source("dumpdata.R") storage.mode(x.hc$merge) <- "integer" plot(x.hc) (R-1.4.1 compiled from source on WinNT4.) Andy > -----Original Message----- > From: Hugh Chipman [mailto:hachipma at icarus.math.uwaterloo.ca] > Sent: Wednesday, February 20, 2002 5:32 PM > To: andy_liaw at merck.com > Cc: r-help at stat.math.ethz.ch

I really want to do this: abline( a=tan(-kT*pi/180), b=kY-tan(-kT*pi/180)*kX ) where kX,kY and kT are vectors of equal length. But I can't do that with abline unless I use a loop, and I haven't figured out the least unelegant way of writing the loop yet. So is there a way to do this without a loop? Or if I am to resort to the loop, what's the best way of doing it considering that I

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

Here what one of my users sometimes gets in logs when using IMAP: dovecot: IMAP(skribtsov at pawlin.mass.hc.ru): Disconnected in IDLE dovecot: IMAP(skribtsov at pawlin.mass.hc.ru): Maildir /usr/local/mail/pawlin.mass.hc.ru/skribtsov/Maildir sync: UID inserted in the middle of mailbox (59 > 16, file = 1198267793.H747026P68033.mail5.hc.ru:2,RS) dovecot: IMAP(skribtsov at pawlin.mass.hc.ru):

Hi all, I have a csv matrix "KT.csv" and it has Inf and NA I want to calculate the mean of each row so I use rowMeans(KT,na.rm = TRUE) but with this Inf cannot be omminted. I?m trying to use before running rowMeans(KT,na.rm = TRUE) KT<-range(KT,finite=TRUE) but it doesn?t works... Do you know a simple way to ommit Inf en the calculations? Many thanks. I have tried also to

Dear R Helpers, I read carefully the documentation and all postings on the hclust and cutree functions, however some aspects of the tree ordering and cluster assignment performed by these functions remain unclear to me, so I would very much appreciate your help in making sure I get them right. Here is an example, with values chosen to illustrate the problems. I have a set of five profiles

Hi, We are trying to interpret the clusters generated by hclust method of R "stats" package. The problem here is when i get the hc$order then there is some order, while exporting to file that order is lost. Here is the example code and their results: > hc <- hclust(dist(USArrests), "ave") > plot(hc) > hc$label [1] "Alabama" "Alaska"

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Add usb-ver format check to "usb-hc-create". In original file, "usb-hc-create" allows usb-ver parameter as "2/2.0/2.0aaa". In low level hc create, it only uses the integer part (that is "2"), so there is no problem. But 2/2.0/2.0aaa will be saved into VM config. After that, while doing "usb-list", it cannot handle "2.0/2.0aaa" and will

2017-09-07 15:04 GMT+02:00 Sami Ketola <sami.ketola at dovecot.fi>: > > > On 7 Sep 2017, at 16.03, Antoine Nguyen <ngu.antoine at gmail.com> wrote: > > > > 2017-09-07 14:29 GMT+02:00 Aki Tuomi <aki.tuomi at dovecot.fi>: > > > >> > >> > >> On 07.09.2017 15:26, Antoine Nguyen wrote: > >>> Hi all, > >>>

https://bugzilla.mindrot.org/show_bug.cgi?id=2680 Bug ID: 2680 Summary: Regression in server-sig-algs offer in 7.4p1 (Deprecation of SHA1 is not being enforced) Product: Portable OpenSSH Version: 7.4p1 Hardware: Other OS: Linux Status: NEW Severity: enhancement Priority: P5

library(mva) data(USArrests) hc <- hclust(dist(USArrests), "ave") plot(hc) # OK dump(c("hc"), "tst") rm(hc) source("tst") plot(hc) # Error in plot.hclust(hc) : invalid dendrogram input The same problem occurs with dput/dget --please do not edit the information below-- Version: platform =

Hi, I'm trying to fit nonlinear mixed effects model using nlme function but getting an error message. Here is what I have: fitted_model = nlme(scores~spline(b1,b2,b3,kt,time), fixed = list(b1~1, b2~1, b3~1, kt~1), random = b1+b2+b3~1, groups= ~id, data = sdat, start = c(b1=3.5,b2=2,b3=.60,kt=3.5),verbose=T) Error: Error in

Dear R Community, I am trying to create an heatmap for the following set of data: ##example of data matrix o4 V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11 V12 V13 V14 V15 V16 V17 V18 green 27 28 29 29 28 28 26 25 25 23 23 22 22 21 21 22 22 22 yellow 6 8 8 7 7 7 6 6 6 7 7 7 6 6 6 6 6 5 red 15 15 15 15 15 15 14 13 12 11 12 10 9 8 7 6 8 9 pink

Can anyone explain this behavior? Essentially, I've created a short file to be read in via source() that gets some descriptive information on a series of variables in a data frame. For each variable, I do three things: print('last.hc.actors') quantile(last.hc.actors,probs=seq(0,1,0.1),na.rm=T) stem(last.hc.actors) where the variable name is (in this case) last.hc.actors. All that

* Antoine Nguyen [2017-09-07 15:13]: > 2017-09-07 15:04 GMT+02:00 Sami Ketola <sami.ketola at dovecot.fi>: > > > > > > On 7 Sep 2017, at 16.03, Antoine Nguyen <ngu.antoine at gmail.com> wrote: > > > > > > 2017-09-07 14:29 GMT+02:00 Aki Tuomi <aki.tuomi at dovecot.fi>: > > > > > >> > > >> > > >>